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Updated the custom_models.md changed cross_entropy code (#33118)

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S M Jishanul Islam
2024-08-26 17:15:43 +06:00
committed by GitHub
parent 0a7af19f4d
commit 8defc95df3
7 changed files with 7 additions and 7 deletions
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2
docs/source/en/custom_models.md
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@@ -185,7 +185,7 @@ class ResnetModelForImageClassification(PreTrainedModel):
def forward(self, tensor, labels=None):
logits = self.model(tensor)
if labels is not None:
loss = torch.nn.cross_entropy(logits, labels)
loss = torch.nn.functional.cross_entropy(logits, labels)
return {"loss": loss, "logits": logits}
return {"logits": logits}
```

2
docs/source/es/custom_models.md
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@@ -173,7 +173,7 @@ class ResnetModelForImageClassification(PreTrainedModel):
def forward(self, tensor, labels=None):
logits = self.model(tensor)
if labels is not None:
loss = torch.nn.cross_entropy(logits, labels)
loss = torch.nn.functional.cross_entropy(logits, labels)
return {"loss": loss, "logits": logits}
return {"logits": logits}
```

2
docs/source/it/custom_models.md
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@@ -174,7 +174,7 @@ class ResnetModelForImageClassification(PreTrainedModel):
def forward(self, tensor, labels=None):
logits = self.model(tensor)
if labels is not None:
loss = torch.nn.cross_entropy(logits, labels)
loss = torch.nn.functional.cross_entropy(logits, labels)
return {"loss": loss, "logits": logits}
return {"logits": logits}
```

2
docs/source/ja/custom_models.md
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@@ -161,7 +161,7 @@ class ResnetModelForImageClassification(PreTrainedModel):
def forward(self, tensor, labels=None):
logits = self.model(tensor)
if labels is not None:
loss = torch.nn.cross_entropy(logits, labels)
loss = torch.nn.functional.cross_entropy(logits, labels)
return {"loss": loss, "logits": logits}
return {"logits": logits}
```

2
docs/source/ko/custom_models.md
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@@ -169,7 +169,7 @@ class ResnetModelForImageClassification(PreTrainedModel):
def forward(self, tensor, labels=None):
logits = self.model(tensor)
if labels is not None:
loss = torch.nn.cross_entropy(logits, labels)
loss = torch.nn.functional.cross_entropy(logits, labels)
return {"loss": loss, "logits": logits}
return {"logits": logits}
```

2
docs/source/pt/custom_models.md
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@@ -173,7 +173,7 @@ class ResnetModelForImageClassification(PreTrainedModel):
def forward(self, tensor, labels=None):
logits = self.model(tensor)
if labels is not None:
loss = torch.nn.cross_entropy(logits, labels)
loss = torch.nn.functional.cross_entropy(logits, labels)
return {"loss": loss, "logits": logits}
return {"logits": logits}
```

2
docs/source/zh/custom_models.md
View File

@@ -154,7 +154,7 @@ class ResnetModelForImageClassification(PreTrainedModel):
def forward(self, tensor, labels=None):
logits = self.model(tensor)
if labels is not None:
loss = torch.nn.cross_entropy(logits, labels)
loss = torch.nn.functional.cross_entropy(logits, labels)
return {"loss": loss, "logits": logits}
return {"logits": logits}
```