mirror of
https://github.com/huggingface/transformers.git
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19420fd99e
* move test model folders (TODO: fix imports and others) * fix (potentially partially) imports (in model test modules) * fix (potentially partially) imports (in tokenization test modules) * fix (potentially partially) imports (in feature extraction test modules) * fix import utils.test_modeling_tf_core * fix path ../fixtures/ * fix imports about generation.test_generation_flax_utils * fix more imports * fix fixture path * fix get_test_dir * update module_to_test_file * fix get_tests_dir from wrong transformers.utils * update config.yml (CircleCI) * fix style * remove missing imports * update new model script * update check_repo * update SPECIAL_MODULE_TO_TEST_MAP * fix style * add __init__ * update self-scheduled * fix add_new_model scripts * check one way to get location back * python setup.py build install * fix import in test auto * update self-scheduled.yml * update slack notification script * Add comments about artifact names * fix for yolos Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
86 lines
2.6 KiB
Python
86 lines
2.6 KiB
Python
# coding=utf-8
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# Copyright 2020 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 os
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import unittest
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from transformers import is_torch_available
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from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
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if is_torch_available():
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import torch
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from transformers import GPT2LMHeadModel
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@require_torch
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@require_sentencepiece
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@require_tokenizers
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class MegatronGPT2IntegrationTest(unittest.TestCase):
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@slow
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@unittest.skip("Model is not available.")
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def test_inference_no_head(self):
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directory = "nvidia/megatron-gpt2-345m/"
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if "MYDIR" in os.environ:
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directory = os.path.join(os.environ["MYDIR"], directory)
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model = GPT2LMHeadModel.from_pretrained(directory)
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model.to(torch_device)
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model.half()
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input_ids = torch.tensor(
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[[101, 7110, 1005, 1056, 2023, 11333, 17413, 1029, 102]],
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device=torch_device,
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dtype=torch.long,
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)
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with torch.no_grad():
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output = model(input_ids).logits
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expected_shape = torch.Size((1, 9, 50257))
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self.assertEqual(output.shape, expected_shape)
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expected_diag = torch.tensor(
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[
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4.9414,
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-0.2920,
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-1.2148,
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-4.0273,
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-0.5161,
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-5.2109,
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-1.2412,
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-1.8301,
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-1.7734,
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-4.7148,
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-0.2317,
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-1.0811,
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-2.1777,
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0.4141,
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-3.7969,
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-4.0586,
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-2.5332,
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-3.3809,
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4.3867,
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],
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device=torch_device,
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dtype=torch.half,
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)
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for i in range(19):
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r, c = 8 * i // 17, 2792 * i # along the diagonal
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computed, expected = output[0, r, c], expected_diag[i]
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msg = f"row={r} col={c} computed={computed} expected={expected}"
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self.assertAlmostEqual(computed, expected, delta=1e-4, msg=msg)
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