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192 | 192 |
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193 | 193 | Args:
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194 | 194 | include_top: Whether to include the fully-connected
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195 |
| - layer at the top of the network. Defaults to True. |
| 195 | + layer at the top of the network. Defaults to `True`. |
196 | 196 | weights: One of `None` (random initialization),
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197 | 197 | 'imagenet' (pre-training on ImageNet),
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198 | 198 | or the path to the weights file to be loaded. Defaults to 'imagenet'.
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203 | 203 | if `include_top` is False.
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204 | 204 | It should have exactly 3 inputs channels.
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205 | 205 | pooling: Optional pooling mode for feature extraction
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206 |
| - when `include_top` is `False`. Defaults to None. |
| 206 | + when `include_top` is `False`. Defaults to `None`. |
207 | 207 | - `None` means that the output of the model will be
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208 | 208 | the 4D tensor output of the
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209 | 209 | last convolutional layer.
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|
215 | 215 | be applied.
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216 | 216 | classes: Optional number of classes to classify images
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217 | 217 | into, only to be specified if `include_top` is True, and
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218 |
| - if no `weights` argument is specified. Defaults to 1000 (number of |
219 |
| - ImageNet classes). |
| 218 | + if no `weights` argument is specified. 1000 is how many |
| 219 | + ImageNet classes there are. Defaults to `1000`. |
220 | 220 | classifier_activation: A `str` or callable. The activation function to use
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221 | 221 | on the "top" layer. Ignored unless `include_top=True`. Set
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222 | 222 | `classifier_activation=None` to return the logits of the "top" layer.
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@@ -852,10 +852,10 @@ def preprocess_input(x, data_format=None):
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852 | 852 |
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853 | 853 | Args:
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854 | 854 | x: A floating point `numpy.array` or a `tf.Tensor`.
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855 |
| - data_format: Optional data format of the image tensor/array. Defaults to |
856 |
| - None, in which case the global setting |
857 |
| - `tf.keras.backend.image_data_format()` is used (unless you changed it, |
858 |
| - it defaults to "channels_last").{mode} |
| 855 | + data_format: Optional data format of the image tensor/array. `None` means |
| 856 | + the global setting `tf.keras.backend.image_data_format()` is used |
| 857 | + (unless you changed it, it uses "channels_last").{mode}. |
| 858 | + Defaults to `None`. |
859 | 859 |
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860 | 860 | Returns:
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861 | 861 | Unchanged `numpy.array` or `tf.Tensor`.
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