766 lines
44 KiB
Python
766 lines
44 KiB
Python
# Copyright 2021 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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import timeout_decorator # noqa
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from transformers import BartConfig, BartTokenizer, is_flax_available
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from transformers.testing_utils import require_flax, slow
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from ...generation.test_flax_utils import FlaxGenerationTesterMixin
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from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
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if is_flax_available():
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import os
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# The slow tests are often failing with OOM error on GPU
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# This makes JAX allocate exactly what is needed on demand, and deallocate memory that is no longer needed
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# but will be slower as stated here https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html
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os.environ["XLA_PYTHON_CLIENT_ALLOCATOR"] = "platform"
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import jax
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import jax.numpy as jnp
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from transformers.models.bart.modeling_flax_bart import (
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FlaxBartForConditionalGeneration,
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FlaxBartForQuestionAnswering,
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FlaxBartForSequenceClassification,
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FlaxBartModel,
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shift_tokens_right,
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)
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def prepare_bart_inputs_dict(
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config,
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input_ids,
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decoder_input_ids=None,
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attention_mask=None,
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decoder_attention_mask=None,
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head_mask=None,
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decoder_head_mask=None,
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cross_attn_head_mask=None,
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):
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if attention_mask is None:
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attention_mask = np.where(input_ids != config.pad_token_id, 1, 0)
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if decoder_attention_mask is None:
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decoder_attention_mask = np.where(decoder_input_ids != config.pad_token_id, 1, 0)
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if head_mask is None:
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head_mask = np.ones((config.encoder_layers, config.encoder_attention_heads))
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if decoder_head_mask is None:
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decoder_head_mask = np.ones((config.decoder_layers, config.decoder_attention_heads))
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if cross_attn_head_mask is None:
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cross_attn_head_mask = np.ones((config.decoder_layers, config.decoder_attention_heads))
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return {
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"input_ids": input_ids,
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"decoder_input_ids": decoder_input_ids,
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"attention_mask": attention_mask,
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"decoder_attention_mask": attention_mask,
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}
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class FlaxBartModelTester:
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def __init__(
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self,
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parent,
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batch_size=13,
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seq_length=7,
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is_training=True,
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use_labels=False,
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vocab_size=99,
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hidden_size=16,
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num_hidden_layers=2,
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num_attention_heads=4,
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intermediate_size=4,
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hidden_act="gelu",
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hidden_dropout_prob=0.1,
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attention_probs_dropout_prob=0.1,
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max_position_embeddings=32,
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eos_token_id=2,
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pad_token_id=1,
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bos_token_id=0,
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initializer_range=0.02,
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):
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self.parent = parent
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self.batch_size = batch_size
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self.seq_length = seq_length
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self.is_training = is_training
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self.use_labels = use_labels
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self.vocab_size = vocab_size
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self.hidden_size = hidden_size
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self.num_hidden_layers = num_hidden_layers
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self.num_attention_heads = num_attention_heads
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self.intermediate_size = intermediate_size
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self.hidden_act = hidden_act
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self.hidden_dropout_prob = hidden_dropout_prob
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self.attention_probs_dropout_prob = attention_probs_dropout_prob
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self.max_position_embeddings = max_position_embeddings
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self.eos_token_id = eos_token_id
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self.pad_token_id = pad_token_id
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self.bos_token_id = bos_token_id
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self.initializer_range = initializer_range
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def prepare_config_and_inputs(self):
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input_ids = np.clip(ids_tensor([self.batch_size, self.seq_length - 1], self.vocab_size), 3, self.vocab_size)
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input_ids = np.concatenate((input_ids, 2 * np.ones((self.batch_size, 1), dtype=np.int64)), -1)
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decoder_input_ids = shift_tokens_right(input_ids, 1, 2)
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config = BartConfig(
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vocab_size=self.vocab_size,
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d_model=self.hidden_size,
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encoder_layers=self.num_hidden_layers,
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decoder_layers=self.num_hidden_layers,
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encoder_attention_heads=self.num_attention_heads,
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decoder_attention_heads=self.num_attention_heads,
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encoder_ffn_dim=self.intermediate_size,
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decoder_ffn_dim=self.intermediate_size,
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dropout=self.hidden_dropout_prob,
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attention_dropout=self.attention_probs_dropout_prob,
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max_position_embeddings=self.max_position_embeddings,
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eos_token_id=self.eos_token_id,
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bos_token_id=self.bos_token_id,
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pad_token_id=self.pad_token_id,
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initializer_range=self.initializer_range,
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use_cache=False,
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)
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inputs_dict = prepare_bart_inputs_dict(config, input_ids, decoder_input_ids)
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return config, inputs_dict
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def prepare_config_and_inputs_for_common(self):
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config, inputs_dict = self.prepare_config_and_inputs()
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return config, inputs_dict
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def check_use_cache_forward(self, model_class_name, config, inputs_dict):
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max_decoder_length = 20
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model = model_class_name(config)
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encoder_outputs = model.encode(inputs_dict["input_ids"])
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decoder_input_ids, decoder_attention_mask = (
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inputs_dict["decoder_input_ids"],
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inputs_dict["decoder_attention_mask"],
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)
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past_key_values = model.init_cache(decoder_input_ids.shape[0], max_decoder_length, encoder_outputs)
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decoder_attention_mask = jnp.ones((decoder_input_ids.shape[0], max_decoder_length), dtype="i4")
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decoder_position_ids = jnp.broadcast_to(
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jnp.arange(decoder_input_ids.shape[-1] - 1)[None, :],
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(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1),
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)
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outputs_cache = model.decode(
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decoder_input_ids[:, :-1],
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encoder_outputs,
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decoder_attention_mask=decoder_attention_mask,
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past_key_values=past_key_values,
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decoder_position_ids=decoder_position_ids,
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)
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decoder_position_ids = jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]], dtype="i4")
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outputs_cache_next = model.decode(
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decoder_input_ids[:, -1:],
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encoder_outputs,
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decoder_attention_mask=decoder_attention_mask,
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past_key_values=outputs_cache.past_key_values,
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decoder_position_ids=decoder_position_ids,
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)
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outputs = model.decode(decoder_input_ids, encoder_outputs)
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diff = np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])))
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self.parent.assertTrue(diff < 1e-3, msg=f"Max diff is {diff}")
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def check_use_cache_forward_with_attn_mask(self, model_class_name, config, inputs_dict):
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max_decoder_length = 20
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model = model_class_name(config)
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encoder_outputs = model.encode(inputs_dict["input_ids"])
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decoder_input_ids, decoder_attention_mask = (
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inputs_dict["decoder_input_ids"],
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inputs_dict["decoder_attention_mask"],
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)
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decoder_attention_mask_cache = jnp.concatenate(
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[
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decoder_attention_mask,
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jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1])),
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],
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axis=-1,
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)
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past_key_values = model.init_cache(decoder_input_ids.shape[0], max_decoder_length, encoder_outputs)
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decoder_position_ids = jnp.broadcast_to(
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jnp.arange(decoder_input_ids.shape[-1] - 1)[None, :],
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(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1),
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)
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outputs_cache = model.decode(
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decoder_input_ids[:, :-1],
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encoder_outputs,
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decoder_attention_mask=decoder_attention_mask_cache,
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past_key_values=past_key_values,
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decoder_position_ids=decoder_position_ids,
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)
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decoder_position_ids = jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]], dtype="i4")
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outputs_cache_next = model.decode(
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decoder_input_ids[:, -1:],
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encoder_outputs,
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past_key_values=outputs_cache.past_key_values,
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decoder_attention_mask=decoder_attention_mask_cache,
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decoder_position_ids=decoder_position_ids,
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)
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outputs = model.decode(decoder_input_ids, encoder_outputs, decoder_attention_mask=decoder_attention_mask)
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diff = np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])))
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self.parent.assertTrue(diff < 1e-3, msg=f"Max diff is {diff}")
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@require_flax
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class BartHeadTests(unittest.TestCase):
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vocab_size = 99
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def _get_config_and_data(self):
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input_ids = np.array(
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[
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[71, 82, 18, 33, 46, 91, 2],
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[68, 34, 26, 58, 30, 82, 2],
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[5, 97, 17, 39, 94, 40, 2],
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[76, 83, 94, 25, 70, 78, 2],
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[87, 59, 41, 35, 48, 66, 2],
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[55, 13, 16, 58, 5, 2, 1], # note padding
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[64, 27, 31, 51, 12, 75, 2],
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[52, 64, 86, 17, 83, 39, 2],
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[48, 61, 9, 24, 71, 82, 2],
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[26, 1, 60, 48, 22, 13, 2],
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[21, 5, 62, 28, 14, 76, 2],
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[45, 98, 37, 86, 59, 48, 2],
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[70, 70, 50, 9, 28, 0, 2],
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],
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dtype=np.int64,
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)
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batch_size = input_ids.shape[0]
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config = BartConfig(
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vocab_size=self.vocab_size,
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d_model=24,
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encoder_layers=2,
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decoder_layers=2,
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encoder_attention_heads=2,
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decoder_attention_heads=2,
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encoder_ffn_dim=32,
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decoder_ffn_dim=32,
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max_position_embeddings=48,
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eos_token_id=2,
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pad_token_id=1,
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bos_token_id=0,
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)
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return config, input_ids, batch_size
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def test_sequence_classification_forward(self):
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config, input_ids, batch_size = self._get_config_and_data()
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model = FlaxBartForSequenceClassification(config)
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outputs = model(input_ids=input_ids, decoder_input_ids=input_ids)
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expected_shape = (batch_size, config.num_labels)
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self.assertEqual(outputs["logits"].shape, expected_shape)
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def test_question_answering_forward(self):
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config, input_ids, batch_size = self._get_config_and_data()
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model = FlaxBartForQuestionAnswering(config)
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outputs = model(input_ids=input_ids)
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self.assertEqual(outputs["start_logits"].shape, input_ids.shape)
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self.assertEqual(outputs["end_logits"].shape, input_ids.shape)
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# @timeout_decorator.timeout(1) # not working with the decorator so far
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def test_lm_forward(self):
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config, input_ids, batch_size = self._get_config_and_data()
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lm_model = FlaxBartForConditionalGeneration(config)
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outputs = lm_model(input_ids=input_ids)
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expected_shape = (batch_size, input_ids.shape[1], config.vocab_size)
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self.assertEqual(outputs["logits"].shape, expected_shape)
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def test_lm_uneven_forward(self):
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config = BartConfig(
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vocab_size=self.vocab_size,
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d_model=14,
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encoder_layers=2,
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decoder_layers=2,
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encoder_attention_heads=2,
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decoder_attention_heads=2,
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encoder_ffn_dim=8,
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decoder_ffn_dim=8,
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max_position_embeddings=48,
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)
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lm_model = FlaxBartForConditionalGeneration(config)
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context = np.array([[71, 82, 18, 33, 46, 91, 2], [68, 34, 26, 58, 30, 2, 1]], dtype=np.int64)
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summary = np.array([[82, 71, 82, 18, 2], [58, 68, 2, 1, 1]], dtype=np.int64)
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outputs = lm_model(input_ids=context, decoder_input_ids=summary)
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expected_shape = (*summary.shape, config.vocab_size)
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self.assertEqual(outputs["logits"].shape, expected_shape)
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def test_shift_tokens_right(self):
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input_ids = np.array([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]], dtype=np.int64)
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shifted = shift_tokens_right(input_ids, 1, 2)
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n_pad_before = np.equal(input_ids, 1).astype(np.float32).sum()
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n_pad_after = np.equal(shifted, 1).astype(np.float32).sum()
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self.assertEqual(shifted.shape, input_ids.shape)
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self.assertEqual(n_pad_after, n_pad_before - 1)
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self.assertTrue(np.equal(shifted[:, 0], 2).all())
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@require_flax
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class FlaxBartModelTest(FlaxModelTesterMixin, unittest.TestCase, FlaxGenerationTesterMixin):
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is_encoder_decoder = True
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all_model_classes = (
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(
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FlaxBartModel,
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FlaxBartForConditionalGeneration,
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FlaxBartForSequenceClassification,
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FlaxBartForQuestionAnswering,
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)
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if is_flax_available()
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else ()
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)
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all_generative_model_classes = (FlaxBartForConditionalGeneration,) if is_flax_available() else ()
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def setUp(self):
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self.model_tester = FlaxBartModelTester(self)
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def test_use_cache_forward(self):
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config, inputs_dict = self.model_tester.prepare_config_and_inputs()
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for model_class in self.all_model_classes:
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self.model_tester.check_use_cache_forward(model_class, config, inputs_dict)
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def test_use_cache_forward_with_attn_mask(self):
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config, inputs_dict = self.model_tester.prepare_config_and_inputs()
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for model_class in self.all_model_classes:
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self.model_tester.check_use_cache_forward_with_attn_mask(model_class, config, inputs_dict)
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def test_encode(self):
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config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
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for model_class in self.all_model_classes:
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with self.subTest(model_class.__name__):
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prepared_inputs_dict = self._prepare_for_class(inputs_dict, model_class)
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model = model_class(config)
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@jax.jit
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def encode_jitted(input_ids, attention_mask=None, **kwargs):
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return model.encode(input_ids=input_ids, attention_mask=attention_mask)
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with self.subTest("JIT Enabled"):
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jitted_outputs = encode_jitted(**prepared_inputs_dict).to_tuple()
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with self.subTest("JIT Disabled"):
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with jax.disable_jit():
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outputs = encode_jitted(**prepared_inputs_dict).to_tuple()
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self.assertEqual(len(outputs), len(jitted_outputs))
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for jitted_output, output in zip(jitted_outputs, outputs):
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self.assertEqual(jitted_output.shape, output.shape)
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def test_decode(self):
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config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
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for model_class in self.all_model_classes:
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with self.subTest(model_class.__name__):
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model = model_class(config)
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encoder_outputs = model.encode(inputs_dict["input_ids"], inputs_dict["attention_mask"])
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prepared_inputs_dict = {
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"decoder_input_ids": inputs_dict["decoder_input_ids"],
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"decoder_attention_mask": inputs_dict["decoder_attention_mask"],
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"encoder_outputs": encoder_outputs,
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}
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@jax.jit
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def decode_jitted(decoder_input_ids, decoder_attention_mask, encoder_outputs):
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return model.decode(
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decoder_input_ids=decoder_input_ids,
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decoder_attention_mask=decoder_attention_mask,
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encoder_outputs=encoder_outputs,
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)
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with self.subTest("JIT Enabled"):
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jitted_outputs = decode_jitted(**prepared_inputs_dict).to_tuple()
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with self.subTest("JIT Disabled"):
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with jax.disable_jit():
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outputs = decode_jitted(**prepared_inputs_dict).to_tuple()
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self.assertEqual(len(outputs), len(jitted_outputs))
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for jitted_output, output in zip(jitted_outputs, outputs):
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self.assertEqual(jitted_output.shape, output.shape)
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@slow
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def test_model_from_pretrained(self):
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for model_class_name in self.all_model_classes:
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model = model_class_name.from_pretrained("facebook/bart-base", from_pt=True)
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# FlaxBartForSequenceClassification expects eos token in input_ids
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input_ids = np.ones((1, 1)) * model.config.eos_token_id
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outputs = model(input_ids)
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self.assertIsNotNone(outputs)
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@slow
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def test_summarization_fast(self):
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model = FlaxBartForConditionalGeneration.from_pretrained("sshleifer/distilbart-cnn-6-6")
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tokenizer = BartTokenizer.from_pretrained("sshleifer/distilbart-cnn-6-6")
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input_str = (
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"This sentence is made of three parts. Each part is important on its own. One part is about animals, the"
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" other part about planes, and the last part about housing."
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)
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input_ids = tokenizer(input_str, return_tensors="np").input_ids
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sequences = model.generate(input_ids, num_beams=2, min_length=None, max_length=20).sequences
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output_str = tokenizer.batch_decode(sequences)[0]
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assert (
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output_str == "</s><s>This sentence is made of three parts. One part is about animals, the other part</s>"
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)
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@slow
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def test_cnn_summarization_same_as_fairseq(self):
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model = FlaxBartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
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tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
|
|
|
|
FRANCE_ARTICLE = ( # @noq
|
|
" Marseille, France (CNN)The French prosecutor leading an investigation into the crash of Germanwings"
|
|
" Flight 9525 insisted Wednesday that he was not aware of any video footage from on board the plane."
|
|
' Marseille prosecutor Brice Robin told CNN that "so far no videos were used in the crash investigation."'
|
|
' He added, "A person who has such a video needs to immediately give it to the investigators." Robin\'s'
|
|
" comments follow claims by two magazines, German daily Bild and French Paris Match, of a cell phone video"
|
|
" showing the harrowing final seconds from on board Germanwings Flight 9525 as it crashed into the French"
|
|
" Alps. All 150 on board were killed. Paris Match and Bild reported that the video was recovered from a"
|
|
" phone at the wreckage site. The two publications described the supposed video, but did not post it on"
|
|
" their websites. The publications said that they watched the video, which was found by a source close to"
|
|
" the investigation. \"One can hear cries of 'My God' in several languages,\" Paris Match reported."
|
|
' "Metallic banging can also be heard more than three times, perhaps of the pilot trying to open the'
|
|
" cockpit door with a heavy object. Towards the end, after a heavy shake, stronger than the others, the"
|
|
' screaming intensifies. Then nothing." "It is a very disturbing scene," said Julian Reichelt,'
|
|
" editor-in-chief of Bild online. An official with France's accident investigation agency, the BEA, said"
|
|
" the agency is not aware of any such video. Lt. Col. Jean-Marc Menichini, a French Gendarmerie spokesman"
|
|
" in charge of communications on rescue efforts around the Germanwings crash site, told CNN that the"
|
|
' reports were "completely wrong" and "unwarranted." Cell phones have been collected at the site, he said,'
|
|
' but that they "hadn\'t been exploited yet." Menichini said he believed the cell phones would need to be'
|
|
" sent to the Criminal Research Institute in Rosny sous-Bois, near Paris, in order to be analyzed by"
|
|
" specialized technicians working hand-in-hand with investigators. But none of the cell phones found so"
|
|
" far have been sent to the institute, Menichini said. Asked whether staff involved in the search could"
|
|
' have leaked a memory card to the media, Menichini answered with a categorical "no." Reichelt told "Erin'
|
|
' Burnett: Outfront" that he had watched the video and stood by the report, saying Bild and Paris Match'
|
|
' are "very confident" that the clip is real. He noted that investigators only revealed they\'d recovered'
|
|
' cell phones from the crash site after Bild and Paris Match published their reports. "That is something'
|
|
" we did not know before. ... Overall we can say many things of the investigation weren't revealed by the"
|
|
' investigation at the beginning," he said. What was mental state of Germanwings co-pilot? German airline'
|
|
" Lufthansa confirmed Tuesday that co-pilot Andreas Lubitz had battled depression years before he took the"
|
|
" controls of Germanwings Flight 9525, which he's accused of deliberately crashing last week in the"
|
|
' French Alps. Lubitz told his Lufthansa flight training school in 2009 that he had a "previous episode of'
|
|
' severe depression," the airline said Tuesday. Email correspondence between Lubitz and the school'
|
|
" discovered in an internal investigation, Lufthansa said, included medical documents he submitted in"
|
|
" connection with resuming his flight training. The announcement indicates that Lufthansa, the parent"
|
|
" company of Germanwings, knew of Lubitz's battle with depression, allowed him to continue training and"
|
|
" ultimately put him in the cockpit. Lufthansa, whose CEO Carsten Spohr previously said Lubitz was 100%"
|
|
' fit to fly, described its statement Tuesday as a "swift and seamless clarification" and said it was'
|
|
" sharing the information and documents -- including training and medical records -- with public"
|
|
" prosecutors. Spohr traveled to the crash site Wednesday, where recovery teams have been working for the"
|
|
" past week to recover human remains and plane debris scattered across a steep mountainside. He saw the"
|
|
" crisis center set up in Seyne-les-Alpes, laid a wreath in the village of Le Vernet, closer to the crash"
|
|
" site, where grieving families have left flowers at a simple stone memorial. Menichini told CNN late"
|
|
" Tuesday that no visible human remains were left at the site but recovery teams would keep searching."
|
|
" French President Francois Hollande, speaking Tuesday, said that it should be possible to identify all"
|
|
" the victims using DNA analysis by the end of the week, sooner than authorities had previously suggested."
|
|
" In the meantime, the recovery of the victims' personal belongings will start Wednesday, Menichini said."
|
|
" Among those personal belongings could be more cell phones belonging to the 144 passengers and six crew"
|
|
" on board. Check out the latest from our correspondents . The details about Lubitz's correspondence with"
|
|
" the flight school during his training were among several developments as investigators continued to"
|
|
" delve into what caused the crash and Lubitz's possible motive for downing the jet. A Lufthansa"
|
|
" spokesperson told CNN on Tuesday that Lubitz had a valid medical certificate, had passed all his"
|
|
' examinations and "held all the licenses required." Earlier, a spokesman for the prosecutor\'s office in'
|
|
" Dusseldorf, Christoph Kumpa, said medical records reveal Lubitz suffered from suicidal tendencies at"
|
|
" some point before his aviation career and underwent psychotherapy before he got his pilot's license."
|
|
" Kumpa emphasized there's no evidence suggesting Lubitz was suicidal or acting aggressively before the"
|
|
" crash. Investigators are looking into whether Lubitz feared his medical condition would cause him to"
|
|
" lose his pilot's license, a European government official briefed on the investigation told CNN on"
|
|
' Tuesday. While flying was "a big part of his life," the source said, it\'s only one theory being'
|
|
" considered. Another source, a law enforcement official briefed on the investigation, also told CNN that"
|
|
" authorities believe the primary motive for Lubitz to bring down the plane was that he feared he would"
|
|
" not be allowed to fly because of his medical problems. Lubitz's girlfriend told investigators he had"
|
|
" seen an eye doctor and a neuropsychologist, both of whom deemed him unfit to work recently and concluded"
|
|
" he had psychological issues, the European government official said. But no matter what details emerge"
|
|
" about his previous mental health struggles, there's more to the story, said Brian Russell, a forensic"
|
|
' psychologist. "Psychology can explain why somebody would turn rage inward on themselves about the fact'
|
|
" that maybe they weren't going to keep doing their job and they're upset about that and so they're"
|
|
' suicidal," he said. "But there is no mental illness that explains why somebody then feels entitled to'
|
|
" also take that rage and turn it outward on 149 other people who had nothing to do with the person's"
|
|
' problems." Germanwings crash compensation: What we know . Who was the captain of Germanwings Flight'
|
|
" 9525? CNN's Margot Haddad reported from Marseille and Pamela Brown from Dusseldorf, while Laura"
|
|
" Smith-Spark wrote from London. CNN's Frederik Pleitgen, Pamela Boykoff, Antonia Mortensen, Sandrine"
|
|
" Amiel and Anna-Maja Rappard contributed to this report."
|
|
)
|
|
|
|
SHORTER_ARTICLE = (
|
|
" (CNN)The Palestinian Authority officially became the 123rd member of the International Criminal Court on"
|
|
" Wednesday, a step that gives the court jurisdiction over alleged crimes in Palestinian territories. The"
|
|
" formal accession was marked with a ceremony at The Hague, in the Netherlands, where the court is based."
|
|
" The Palestinians signed the ICC's founding Rome Statute in January, when they also accepted its"
|
|
' jurisdiction over alleged crimes committed "in the occupied Palestinian territory, including East'
|
|
' Jerusalem, since June 13, 2014." Later that month, the ICC opened a preliminary examination into the'
|
|
" situation in Palestinian territories, paving the way for possible war crimes investigations against"
|
|
" Israelis. As members of the court, Palestinians may be subject to counter-charges as well. Israel and"
|
|
" the United States, neither of which is an ICC member, opposed the Palestinians' efforts to join the"
|
|
" body. But Palestinian Foreign Minister Riad al-Malki, speaking at Wednesday's ceremony, said it was a"
|
|
' move toward greater justice. "As Palestine formally becomes a State Party to the Rome Statute today, the'
|
|
' world is also a step closer to ending a long era of impunity and injustice," he said, according to an'
|
|
' ICC news release. "Indeed, today brings us closer to our shared goals of justice and peace." Judge'
|
|
" Kuniko Ozaki, a vice president of the ICC, said acceding to the treaty was just the first step for the"
|
|
' Palestinians. "As the Rome Statute today enters into force for the State of Palestine, Palestine'
|
|
" acquires all the rights as well as responsibilities that come with being a State Party to the Statute."
|
|
' These are substantive commitments, which cannot be taken lightly," she said. Rights group Human Rights'
|
|
' Watch welcomed the development. "Governments seeking to penalize Palestine for joining the ICC should'
|
|
" immediately end their pressure, and countries that support universal acceptance of the court's treaty"
|
|
' should speak out to welcome its membership," said Balkees Jarrah, international justice counsel for the'
|
|
" group. \"What's objectionable is the attempts to undermine international justice, not Palestine's"
|
|
' decision to join a treaty to which over 100 countries around the world are members." In January, when'
|
|
" the preliminary ICC examination was opened, Israeli Prime Minister Benjamin Netanyahu described it as an"
|
|
' outrage, saying the court was overstepping its boundaries. The United States also said it "strongly"'
|
|
" disagreed with the court's decision. \"As we have said repeatedly, we do not believe that Palestine is a"
|
|
' state and therefore we do not believe that it is eligible to join the ICC," the State Department said in'
|
|
' a statement. It urged the warring sides to resolve their differences through direct negotiations. "We'
|
|
' will continue to oppose actions against Israel at the ICC as counterproductive to the cause of peace,"'
|
|
" it said. But the ICC begs to differ with the definition of a state for its purposes and refers to the"
|
|
' territories as "Palestine." While a preliminary examination is not a formal investigation, it allows the'
|
|
" court to review evidence and determine whether to investigate suspects on both sides. Prosecutor Fatou"
|
|
' Bensouda said her office would "conduct its analysis in full independence and impartiality." The war'
|
|
" between Israel and Hamas militants in Gaza last summer left more than 2,000 people dead. The inquiry"
|
|
" will include alleged war crimes committed since June. The International Criminal Court was set up in"
|
|
" 2002 to prosecute genocide, crimes against humanity and war crimes. CNN's Vasco Cotovio, Kareem Khadder"
|
|
" and Faith Karimi contributed to this report."
|
|
)
|
|
|
|
# The below article tests that we don't add any hypotheses outside of the top n_beams
|
|
IRAN_ARTICLE = (
|
|
" (CNN)The United States and its negotiating partners reached a very strong framework agreement with Iran"
|
|
" in Lausanne, Switzerland, on Thursday that limits Iran's nuclear program in such a way as to effectively"
|
|
" block it from building a nuclear weapon. Expect pushback anyway, if the recent past is any harbinger."
|
|
" Just last month, in an attempt to head off such an agreement, House Speaker John Boehner invited Israeli"
|
|
" Prime Minister Benjamin Netanyahu to preemptively blast it before Congress, and 47 senators sent a"
|
|
" letter to the Iranian leadership warning them away from a deal. The debate that has already begun since"
|
|
" the announcement of the new framework will likely result in more heat than light. It will not be helped"
|
|
" by the gathering swirl of dubious assumptions and doubtful assertions. Let us address some of these: ."
|
|
" The most misleading assertion, despite universal rejection by experts, is that the negotiations'"
|
|
" objective at the outset was the total elimination of any nuclear program in Iran. That is the position"
|
|
" of Netanyahu and his acolytes in the U.S. Congress. But that is not and never was the objective. If it"
|
|
" had been, there would have been no Iranian team at the negotiating table. Rather, the objective has"
|
|
" always been to structure an agreement or series of agreements so that Iran could not covertly develop a"
|
|
" nuclear arsenal before the United States and its allies could respond. The new framework has exceeded"
|
|
" expectations in achieving that goal. It would reduce Iran's low-enriched uranium stockpile, cut by"
|
|
" two-thirds its number of installed centrifuges and implement a rigorous inspection regime. Another"
|
|
" dubious assumption of opponents is that the Iranian nuclear program is a covert weapons program. Despite"
|
|
" sharp accusations by some in the United States and its allies, Iran denies having such a program, and"
|
|
" U.S. intelligence contends that Iran has not yet made the decision to build a nuclear weapon. Iran's"
|
|
" continued cooperation with International Atomic Energy Agency inspections is further evidence on this"
|
|
" point, and we'll know even more about Iran's program in the coming months and years because of the deal."
|
|
" In fact, the inspections provisions that are part of this agreement are designed to protect against any"
|
|
" covert action by the Iranians. What's more, the rhetoric of some members of Congress has implied that"
|
|
" the negotiations have been between only the United States and Iran (i.e., the 47 senators' letter"
|
|
" warning that a deal might be killed by Congress or a future president). This of course is not the case."
|
|
" The talks were between Iran and the five permanent members of the U.N. Security Council (United States,"
|
|
" United Kingdom, France, China and Russia) plus Germany, dubbed the P5+1. While the United States has"
|
|
" played a leading role in the effort, it negotiated the terms alongside its partners. If the agreement"
|
|
" reached by the P5+1 is rejected by Congress, it could result in an unraveling of the sanctions on Iran"
|
|
" and threaten NATO cohesion in other areas. Another questionable assertion is that this agreement"
|
|
" contains a sunset clause, after which Iran will be free to do as it pleases. Again, this is not the"
|
|
" case. Some of the restrictions on Iran's nuclear activities, such as uranium enrichment, will be eased"
|
|
" or eliminated over time, as long as 15 years. But most importantly, the framework agreement includes"
|
|
" Iran's ratification of the Additional Protocol, which allows IAEA inspectors expanded access to nuclear"
|
|
" sites both declared and nondeclared. This provision will be permanent. It does not sunset. Thus, going"
|
|
" forward, if Iran decides to enrich uranium to weapons-grade levels, monitors will be able to detect such"
|
|
" a move in a matter of days and alert the U.N. Security Council. Many in Congress have said that the"
|
|
' agreement should be a formal treaty requiring the Senate to "advise and consent." But the issue is not'
|
|
" suited for a treaty. Treaties impose equivalent obligations on all signatories. For example, the New"
|
|
" START treaty limits Russia and the United States to 1,550 deployed strategic warheads. But any agreement"
|
|
" with Iran will not be so balanced. The restrictions and obligations in the final framework agreement"
|
|
" will be imposed almost exclusively on Iran. The P5+1 are obligated only to ease and eventually remove"
|
|
" most but not all economic sanctions, which were imposed as leverage to gain this final deal. Finally"
|
|
" some insist that any agreement must address Iranian missile programs, human rights violations or support"
|
|
" for Hamas or Hezbollah. As important as these issues are, and they must indeed be addressed, they are"
|
|
" unrelated to the most important aim of a nuclear deal: preventing a nuclear Iran. To include them in"
|
|
" the negotiations would be a poison pill. This agreement should be judged on its merits and on how it"
|
|
" affects the security of our negotiating partners and allies, including Israel. Those judgments should be"
|
|
" fact-based, not based on questionable assertions or dubious assumptions."
|
|
)
|
|
|
|
ARTICLE_SUBWAY = (
|
|
" New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County, New York. A"
|
|
" year later, she got married again in Westchester County, but to a different man and without divorcing"
|
|
" her first husband. Only 18 days after that marriage, she got hitched yet again. Then, Barrientos"
|
|
' declared "I do" five more times, sometimes only within two weeks of each other. In 2010, she married'
|
|
" once more, this time in the Bronx. In an application for a marriage license, she stated it was her"
|
|
' "first and only" marriage. Barrientos, now 39, is facing two criminal counts of "offering a false'
|
|
' instrument for filing in the first degree," referring to her false statements on the 2010 marriage'
|
|
" license application, according to court documents. Prosecutors said the marriages were part of an"
|
|
" immigration scam. On Friday, she pleaded not guilty at State Supreme Court in the Bronx, according to"
|
|
" her attorney, Christopher Wright, who declined to comment further. After leaving court, Barrientos was"
|
|
" arrested and charged with theft of service and criminal trespass for allegedly sneaking into the New"
|
|
" York subway through an emergency exit, said Detective Annette Markowski, a police spokeswoman. In total,"
|
|
" Barrientos has been married 10 times, with nine of her marriages occurring between 1999 and 2002. All"
|
|
" occurred either in Westchester County, Long Island, New Jersey or the Bronx. She is believed to still be"
|
|
" married to four men, and at one time, she was married to eight men at once, prosecutors say. Prosecutors"
|
|
" said the immigration scam involved some of her husbands, who filed for permanent residence status"
|
|
" shortly after the marriages. Any divorces happened only after such filings were approved. It was"
|
|
" unclear whether any of the men will be prosecuted. The case was referred to the Bronx District"
|
|
" Attorney's Office by Immigration and Customs Enforcement and the Department of Homeland Security's"
|
|
' Investigation Division. Seven of the men are from so-called "red-flagged" countries, including Egypt,'
|
|
" Turkey, Georgia, Pakistan and Mali. Her eighth husband, Rashid Rajput, was deported in 2006 to his"
|
|
" native Pakistan after an investigation by the Joint Terrorism Task Force. If convicted, Barrientos faces"
|
|
" up to four years in prison. Her next court appearance is scheduled for May 18."
|
|
)
|
|
|
|
dct = tokenizer.batch_encode_plus(
|
|
[FRANCE_ARTICLE, SHORTER_ARTICLE, IRAN_ARTICLE, ARTICLE_SUBWAY],
|
|
max_length=1024,
|
|
padding="max_length",
|
|
truncation_strategy="only_first",
|
|
truncation=True,
|
|
return_tensors="np",
|
|
)
|
|
|
|
self.assertEqual(1024, dct["input_ids"].shape[1])
|
|
hypotheses_batch = model.generate(
|
|
input_ids=dct["input_ids"],
|
|
attention_mask=dct["attention_mask"],
|
|
num_beams=2,
|
|
).sequences
|
|
assert (hypotheses_batch[:, 1] == 0).all().item()
|
|
|
|
EXPECTED = [
|
|
"A French prosecutor says he is not aware of any video footage from on board the plane. Two German"
|
|
" magazines claim to have found a cell phone video showing the crash. The publications say they watched"
|
|
" the video, which was found by a source close to the investigation. All 150 on board the Germanwings"
|
|
" flight were killed.",
|
|
"Palestinian Authority becomes 123rd member of the International Criminal Court. The move gives the court"
|
|
" jurisdiction over alleged crimes in Palestinian territories. Israel and the United States opposed the"
|
|
" Palestinians' efforts to join the body. But Palestinian Foreign Minister Riad al-Malki said it was a"
|
|
" move toward greater justice.",
|
|
"U.S. and its negotiating partners reached a strong framework agreement with Iran. Peter Bergen: The"
|
|
" debate that has already begun will likely result in more heat than light. Bergen: The most misleading"
|
|
" assertion is that the negotiations' objective at the outset was the total elimination of any nuclear"
|
|
" program.",
|
|
"Liana Barrientos, 39, has been married 10 times, sometimes within two weeks of each other. Prosecutors"
|
|
" say the marriages were part of an immigration scam. She pleaded not guilty at State Supreme Court in the"
|
|
" Bronx on Friday. If convicted, Barrientos faces up to four years in prison.",
|
|
]
|
|
|
|
generated_summaries = tokenizer.batch_decode(
|
|
hypotheses_batch.tolist(), clean_up_tokenization_spaces=True, skip_special_tokens=True
|
|
)
|
|
assert generated_summaries == EXPECTED
|
|
|
|
|
|
class FlaxBartStandaloneDecoderModelTester:
|
|
def __init__(
|
|
self,
|
|
parent,
|
|
batch_size=13,
|
|
seq_length=7,
|
|
is_training=True,
|
|
use_attention_mask=True,
|
|
use_labels=False,
|
|
vocab_size=99,
|
|
hidden_size=16,
|
|
num_hidden_layers=2,
|
|
num_attention_heads=4,
|
|
intermediate_size=4,
|
|
hidden_act="gelu",
|
|
hidden_dropout_prob=0.1,
|
|
attention_probs_dropout_prob=0.1,
|
|
max_position_embeddings=32,
|
|
eos_token_id=2,
|
|
pad_token_id=1,
|
|
bos_token_id=0,
|
|
initializer_range=0.02,
|
|
):
|
|
self.parent = parent
|
|
self.batch_size = batch_size
|
|
self.seq_length = seq_length
|
|
self.is_training = is_training
|
|
self.use_attention_mask = use_attention_mask
|
|
self.use_labels = use_labels
|
|
self.vocab_size = vocab_size
|
|
self.hidden_size = hidden_size
|
|
self.num_hidden_layers = num_hidden_layers
|
|
self.num_attention_heads = num_attention_heads
|
|
self.intermediate_size = intermediate_size
|
|
self.hidden_act = hidden_act
|
|
self.hidden_dropout_prob = hidden_dropout_prob
|
|
self.attention_probs_dropout_prob = attention_probs_dropout_prob
|
|
self.max_position_embeddings = max_position_embeddings
|
|
self.eos_token_id = eos_token_id
|
|
self.pad_token_id = pad_token_id
|
|
self.bos_token_id = bos_token_id
|
|
self.initializer_range = initializer_range
|
|
|
|
def prepare_config_and_inputs(self):
|
|
input_ids = jnp.clip(ids_tensor([self.batch_size, self.seq_length], self.vocab_size), 3, self.vocab_size)
|
|
|
|
attention_mask = None
|
|
if self.use_attention_mask:
|
|
attention_mask = random_attention_mask([self.batch_size, self.seq_length])
|
|
|
|
config = BartConfig(
|
|
vocab_size=self.vocab_size,
|
|
d_model=self.hidden_size,
|
|
encoder_layers=self.num_hidden_layers,
|
|
decoder_layers=self.num_hidden_layers,
|
|
encoder_attention_heads=self.num_attention_heads,
|
|
decoder_attention_heads=self.num_attention_heads,
|
|
encoder_ffn_dim=self.intermediate_size,
|
|
decoder_ffn_dim=self.intermediate_size,
|
|
dropout=self.hidden_dropout_prob,
|
|
attention_dropout=self.attention_probs_dropout_prob,
|
|
max_position_embeddings=self.max_position_embeddings,
|
|
eos_token_id=self.eos_token_id,
|
|
bos_token_id=self.bos_token_id,
|
|
pad_token_id=self.pad_token_id,
|
|
initializer_range=self.initializer_range,
|
|
use_cache=False,
|
|
)
|
|
|
|
return config, input_ids, attention_mask
|
|
|
|
def prepare_config_and_inputs_for_common(self):
|
|
config_and_inputs = self.prepare_config_and_inputs()
|
|
config, input_ids, attention_mask = config_and_inputs
|
|
inputs_dict = {"input_ids": input_ids, "attention_mask": attention_mask}
|
|
return config, inputs_dict
|
|
|
|
def prepare_config_and_inputs_for_decoder(self):
|
|
config, input_ids, attention_mask = self.prepare_config_and_inputs()
|
|
|
|
encoder_hidden_states = floats_tensor([self.batch_size, self.seq_length, self.hidden_size])
|
|
encoder_attention_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2)
|
|
|
|
return (
|
|
config,
|
|
input_ids,
|
|
attention_mask,
|
|
encoder_hidden_states,
|
|
encoder_attention_mask,
|
|
)
|