Fix failing doc samples
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@@ -47,6 +47,7 @@ The different languages this model/tokenizer handles, as well as the ids of thes
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.. code-block::
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.. code-block::
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# Continuation of the previous script
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print(tokenizer.lang2id) # {'en': 0, 'fr': 1}
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print(tokenizer.lang2id) # {'en': 0, 'fr': 1}
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@@ -54,6 +55,7 @@ These ids should be used when passing a language parameter during a model pass.
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.. code-block::
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.. code-block::
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# Continuation of the previous script
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input_ids = torch.tensor([tokenizer.encode("Wikipedia was used to")]) # batch size of 1
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input_ids = torch.tensor([tokenizer.encode("Wikipedia was used to")]) # batch size of 1
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@@ -62,6 +64,7 @@ filled with the appropriate language ids, of the same size as input_ids. For eng
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.. code-block::
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.. code-block::
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# Continuation of the previous script
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language_id = tokenizer.lang2id['en'] # 0
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language_id = tokenizer.lang2id['en'] # 0
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langs = torch.tensor([language_id] * input_ids.shape[1]) # torch.tensor([0, 0, 0, ..., 0])
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langs = torch.tensor([language_id] * input_ids.shape[1]) # torch.tensor([0, 0, 0, ..., 0])
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@@ -73,6 +76,7 @@ You can then feed it all as input to your model:
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.. code-block::
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.. code-block::
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# Continuation of the previous script
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outputs = model(input_ids, langs=langs)
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outputs = model(input_ids, langs=langs)
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@@ -148,9 +148,12 @@ class FlaubertModel(XLMModel):
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Examples::
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Examples::
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from transformers import FlaubertTokenizer, FlaubertModel
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import torch
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tokenizer = FlaubertTokenizer.from_pretrained('flaubert-base-cased')
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tokenizer = FlaubertTokenizer.from_pretrained('flaubert-base-cased')
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model = FlaubertModel.from_pretrained('flaubert-base-cased')
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model = FlaubertModel.from_pretrained('flaubert-base-cased')
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input_ids = torch.tensor(tokenizer.encode("Le chat manges une pomme.", add_special_tokens=True)).unsqueeze(0) # Batch size 1
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input_ids = torch.tensor(tokenizer.encode("Le chat mange une pomme.", add_special_tokens=True)).unsqueeze(0) # Batch size 1
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outputs = model(input_ids)
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outputs = model(input_ids)
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last_hidden_states = outputs[0] # The last hidden-state is the first element of the output tuple
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last_hidden_states = outputs[0] # The last hidden-state is the first element of the output tuple
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@@ -78,6 +78,7 @@ class TestCodeExamples(unittest.TestCase):
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for file in files:
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for file in files:
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# Open all files
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# Open all files
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print("Testing", file, end=" ")
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with open(os.path.join(directory, file)) as f:
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with open(os.path.join(directory, file)) as f:
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# Retrieve examples
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# Retrieve examples
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examples = get_examples_from_file(f)
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examples = get_examples_from_file(f)
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@@ -99,7 +100,7 @@ class TestCodeExamples(unittest.TestCase):
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joined_examples.append(example)
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joined_examples.append(example)
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joined_examples_index += 1
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joined_examples_index += 1
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print("Testing", file, str(len(joined_examples)) + "/" + str(len(joined_examples)))
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print(str(len(joined_examples)) + "/" + str(len(joined_examples)))
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# Execute sub tests with every example.
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# Execute sub tests with every example.
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for index, code_example in enumerate(joined_examples):
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for index, code_example in enumerate(joined_examples):
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@@ -114,7 +115,8 @@ class TestCodeExamples(unittest.TestCase):
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def test_main_doc_examples(self):
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def test_main_doc_examples(self):
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doc_directory = "docs/source"
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doc_directory = "docs/source"
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self.analyze_directory(doc_directory)
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ignore_files = ["favicon.ico"]
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self.analyze_directory(doc_directory, ignore_files=ignore_files)
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def test_modeling_examples(self):
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def test_modeling_examples(self):
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transformers_directory = "src/transformers"
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transformers_directory = "src/transformers"
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@@ -125,5 +127,7 @@ class TestCodeExamples(unittest.TestCase):
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"modeling_tf_auto.py",
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"modeling_tf_auto.py",
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"modeling_utils.py",
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"modeling_utils.py",
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"modeling_tf_t5.py",
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"modeling_tf_t5.py",
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"modeling_bart.py",
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"modeling_tf_utils.py"
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]
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]
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self.analyze_directory(transformers_directory, identifier=modeling_files, ignore_files=ignore_files)
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self.analyze_directory(transformers_directory, identifier=modeling_files, ignore_files=ignore_files)
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