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Fix annotations (#24582)

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* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations

* fix annotations
This commit is contained in:
MS Kim(tony9402)
2023-06-30 03:17:35 +09:00
committed by GitHub
parent c817bc44e2
commit 232c898f9f
26 changed files with 59 additions and 59 deletions
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6
templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_tf_{{cookiecutter.lowercase_modelname}}.py
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@@ -1794,7 +1794,7 @@ class TF{{cookiecutter.camelcase_modelname}}EncoderLayer(tf.keras.layers.Layer):
def call(self, hidden_states: tf.Tensor, attention_mask: tf.Tensor, layer_head_mask: tf.Tensor, training=False):
"""
Args:
hidden_states (`tf.Tensor`): input to the layer of shape *(seq_len, batch, embed_dim)*
hidden_states (`tf.Tensor`): input to the layer of shape *(batch, seq_len, embed_dim)*
attention_mask (`tf.Tensor`): attention mask of size
*(batch, 1, tgt_len, src_len)* where padding elements are indicated by very large negative values.
layer_head_mask (`tf.Tensor`): mask for attention heads in a given layer of size
@@ -1867,10 +1867,10 @@ class TF{{cookiecutter.camelcase_modelname}}DecoderLayer(tf.keras.layers.Layer):
) -> Tuple[tf.Tensor, tf.Tensor, Tuple[Tuple[tf.Tensor]]]:
"""
Args:
hidden_states (`tf.Tensor`): input to the layer of shape *(seq_len, batch, embed_dim)*
hidden_states (`tf.Tensor`): input to the layer of shape *(batch, seq_len, embed_dim)*
attention_mask (`tf.Tensor`): attention mask of size
*(batch, 1, tgt_len, src_len)* where padding elements are indicated by very large negative values.
encoder_hidden_states (`tf.Tensor`): cross attention input to the layer of shape *(seq_len, batch, embed_dim)*
encoder_hidden_states (`tf.Tensor`): cross attention input to the layer of shape *(batch, seq_len, embed_dim)*
encoder_attention_mask (`tf.Tensor`): encoder attention mask of size
*(batch, 1, tgt_len, src_len)* where padding elements are indicated by very large negative values.
layer_head_mask (`tf.Tensor`): mask for attention heads in a given layer of size

6
templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_{{cookiecutter.lowercase_modelname}}.py
View File

@@ -1826,7 +1826,7 @@ class {{cookiecutter.camelcase_modelname}}EncoderLayer(nn.Module):
):
"""
Args:
hidden_states (`torch.FloatTensor`): input to the layer of shape *(seq_len, batch, embed_dim)*
hidden_states (`torch.FloatTensor`): input to the layer of shape *(batch, seq_len, embed_dim)*
attention_mask (`torch.FloatTensor`): attention mask of size
*(batch, 1, tgt_len, src_len)* where padding elements are indicated by very large negative values.
layer_head_mask (`torch.FloatTensor`): mask for attention heads in a given layer of size
@@ -1907,10 +1907,10 @@ class {{cookiecutter.camelcase_modelname}}DecoderLayer(nn.Module):
):
"""
Args:
hidden_states (`torch.FloatTensor`): input to the layer of shape *(seq_len, batch, embed_dim)*
hidden_states (`torch.FloatTensor`): input to the layer of shape *(batch, seq_len, embed_dim)*
attention_mask (`torch.FloatTensor`): attention mask of size
*(batch, 1, tgt_len, src_len)* where padding elements are indicated by very large negative values.
encoder_hidden_states (`torch.FloatTensor`): cross attention input to the layer of shape *(seq_len, batch, embed_dim)*
encoder_hidden_states (`torch.FloatTensor`): cross attention input to the layer of shape *(batch, seq_len, embed_dim)*
encoder_attention_mask (`torch.FloatTensor`): encoder attention mask of size
*(batch, 1, tgt_len, src_len)* where padding elements are indicated by very large negative values.
layer_head_mask (`torch.FloatTensor`): mask for attention heads in a given layer of size