Fixed the segmentation fault in CamemBERT and VIT #6
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tancheng
reviewed
Oct 9, 2024
| @@ -24,6 +24,7 @@ def __init__(self, model_name: str): | |||
| self.layer3 = AutoModelForTokenClassification.from_pretrained(model_name).classifier | |||
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| def forward(self, input): | |||
| x = input.reshape(1, 7, 768) | |||
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Hmmm, I don't see how this works. Shouldn't it be input = instead of x =? And you already did example_input = example_input.reshape(1, 7*768) in line 50 but reshape it back here?
| @@ -44,7 +45,10 @@ def forward(self, input): | |||
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| print("Parsing sentence tokens.") | |||
| example_input = prepare_sentence_tokens(model_name, sentence) | |||
| print(example_input.shape) | |||
| print("example_input shape: ", example_input.shape) | |||
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Can you add comment above this line to show what is the original shape?
tancheng
reviewed
Oct 9, 2024
| @@ -47,6 +47,7 @@ def forward(self, input): | |||
| example_input = prepare_sentence_tokens(model_name, sentence) | |||
| print("example_input shape: ", example_input.shape) | |||
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| # The original example_input shape is [1, 7, 768], now we reshape it into [1, 7*768] | |||
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Can you add an assert here to make sure the shape is [1, 7, 768]?
| @@ -47,6 +47,7 @@ def forward(self, input): | |||
| example_input = prepare_sentence_tokens(model_name, sentence) | |||
| print("example_input shape: ", example_input.shape) | |||
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| # The original example_input shape is [1, 7, 768], now we reshape it into [1, 7*768] | |||
| example_input = example_input.reshape(1, 7*768) | |||
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