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fix a typo in several places (ouput -> output)

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Thomas McColgan 2015-07-16 22:48:38 +02:00
parent 6a4aab453f
commit 71ac4bffd3
1 changed files with 5 additions and 5 deletions
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10
docs/sources/layers/recurrent.md
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@ -11,7 +11,7 @@ Fully connected RNN where output is to fed back to input.
- __Input shape__: 3D tensor with shape: `(nb_samples, timesteps, input_dim)`.
- __Output shape__:
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, ouput_dim)`.
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, output_dim)`.
- else: 2D tensor with shape: `(nb_samples, output_dim)`.
- __Masking__: This layer supports masking for input data with a variable number of timesteps To introduce masks to your data, use an [Embedding](embeddings.md) layer with the `mask_zero` parameter set to `True`.
@ -47,7 +47,7 @@ Not a particularly useful model, included for demonstration purposes.
- __Input shape__: 3D tensor with shape: `(nb_samples, timesteps, input_dim)`.
- __Output shape__:
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, ouput_dim)`.
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, output_dim)`.
- else: 2D tensor with shape: `(nb_samples, output_dim)`.
- __Masking__: This layer supports masking for input data with a variable number of timesteps To introduce masks to your data, use an [Embedding](embeddings.md) layer with the `mask_zero` parameter set to `True`.
@ -82,7 +82,7 @@ Gated Recurrent Unit - Cho et al. 2014.
- __Input shape__: 3D tensor with shape: `(nb_samples, timesteps, input_dim)`.
- __Output shape__:
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, ouput_dim)`.
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, output_dim)`.
- else: 2D tensor with shape: `(nb_samples, output_dim)`.
- __Masking__: This layer supports masking for input data with a variable number of timesteps To introduce masks to your data, use an [Embedding](embeddings.md) layer with the `mask_zero` parameter set to true.
@ -118,7 +118,7 @@ Long-Short Term Memory unit - Hochreiter 1997.
- __Input shape__: 3D tensor with shape: `(nb_samples, timesteps, input_dim)`.
- __Output shape__:
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, ouput_dim)`.
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, output_dim)`.
- else: 2D tensor with shape: `(nb_samples, output_dim)`.
- __Masking__: This layer supports masking for input data with a variable number of timesteps To introduce masks to your data, use an [Embedding](embeddings.md) layer with the `mask_zero` parameter set to true.
@ -156,7 +156,7 @@ Top 3 RNN architectures evolved from the evaluation of thousands of models. Serv
- __Input shape__: 3D tensor with shape: `(nb_samples, timesteps, input_dim)`.
- __Output shape__:
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, ouput_dim)`.
- if `return_sequences`: 3D tensor with shape: `(nb_samples, timesteps, output_dim)`.
- else: 2D tensor with shape: `(nb_samples, output_dim)`.
- __Masking__: This layer supports masking for input data with a variable number of timesteps To introduce masks to your data, use an [Embedding](embeddings.md) layer with the `mask_zero` parameter set to true.