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# coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import shutil
import unittest
from unittest.mock import patch
from transformers.testing_utils import CaptureStd, is_pt_tf_cross_test, require_torch
class CLITest(unittest.TestCase):
@patch("sys.argv", ["fakeprogrampath", "env"])
def test_cli_env(self):
# test transformers-cli env
import transformers.commands.transformers_cli
with CaptureStd() as cs:
transformers.commands.transformers_cli.main()
self.assertIn("Python version", cs.out)
self.assertIn("Platform", cs.out)
self.assertIn("Using distributed or parallel set-up in script?", cs.out)
@is_pt_tf_cross_test
@patch(
"sys.argv", ["fakeprogrampath", "pt-to-tf", "--model-name", "hf-internal-testing/tiny-random-gptj", "--no-pr"]
)
def test_cli_pt_to_tf(self):
import transformers.commands.transformers_cli
shutil.rmtree("/tmp/hf-internal-testing/tiny-random-gptj", ignore_errors=True) # cleans potential past runs
transformers.commands.transformers_cli.main()
self.assertTrue(os.path.exists("/tmp/hf-internal-testing/tiny-random-gptj/tf_model.h5"))
@require_torch
@patch("sys.argv", ["fakeprogrampath", "download", "hf-internal-testing/tiny-random-gptj", "--cache-dir", "/tmp"])
def test_cli_download(self):
import transformers.commands.transformers_cli
# # remove any previously downloaded model to start clean
shutil.rmtree("/tmp/models--hf-internal-testing--tiny-random-gptj", ignore_errors=True)
# run the command
transformers.commands.transformers_cli.main()
# check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--tiny-random-gptj
self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/blobs"))
self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/refs"))
self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/snapshots"))
@require_torch
@patch(
"sys.argv",
[
"fakeprogrampath",
"download",
"hf-internal-testing/test_dynamic_model_with_tokenizer",
"--trust-remote-code",
"--cache-dir",
"/tmp",
],
)
def test_cli_download_trust_remote(self):
import transformers.commands.transformers_cli
# # remove any previously downloaded model to start clean
shutil.rmtree("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer", ignore_errors=True)
# run the command
transformers.commands.transformers_cli.main()
# check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer
self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/blobs"))
self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/refs"))
self.assertTrue(
os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/snapshots")
)