From f577ada969539b3356e1926ea079010e173a5406 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <nobody@tensorflow.org>
Date: Tue, 24 May 2016 17:18:58 -0800
Subject: [PATCH] Update generated Python Op docs. Change: 123168816
---
tensorflow/g3doc/api_docs/python/array_ops.md | 41 ++++++++++++++++---
.../g3doc/api_docs/python/constant_op.md | 4 +-
.../g3doc/api_docs/python/contrib.learn.md | 9 ++--
.../tf.contrib.learn.evaluate.md | 9 ++--
.../functions_and_classes/tf.one_hot.md | 41 ++++++++++++++++---
tensorflow/g3doc/api_docs/python/nn.md | 6 +--
6 files changed, 87 insertions(+), 23 deletions(-)
diff --git a/tensorflow/g3doc/api_docs/python/array_ops.md b/tensorflow/g3doc/api_docs/python/array_ops.md
index 0c6cd7582ec..3662e7eaa3a 100644
--- a/tensorflow/g3doc/api_docs/python/array_ops.md
+++ b/tensorflow/g3doc/api_docs/python/array_ops.md
@@ -1439,14 +1439,21 @@ boolean_mask(tensor, mask) ==> [[1, 2], [5, 6]]
- - -
-### `tf.one_hot(indices, depth, on_value=1, off_value=0, axis=None, dtype=tf.float32, name=None)` {#one_hot}
+### `tf.one_hot(indices, depth, on_value=None, off_value=None, axis=None, dtype=None, name=None)` {#one_hot}
Returns a one-hot tensor.
The locations represented by indices in `indices` take value `on_value`,
-while all other locations take value `off_value`. By default, `on_value` is 1,
-and `off_value` is 0. The type of the output tensor is specified by `dtype`,
-which defaults to `tf.float32`.
+while all other locations take value `off_value`.
+
+`on_value` and `off_value` must have matching data types. If `dtype` is also
+provided, they must be the same data type as specified by `dtype`.
+
+If `on_value` is not provided, it will default to the value `1` with type
+`dtype`
+
+If `off_value` is not provided, it will default to the value `0` with type
+`dtype`
If the input `indices` is rank `N`, the output will have rank `N+1`. The
new axis is created at dimension `axis` (default: the new axis is appended
@@ -1468,6 +1475,13 @@ shape will be:
depth x batch x features if axis == 0
```
+If `dtype` is not provided, it will attempt to assume the data type of
+`on_value` or `off_value`, if one or both are passed in. If none of
+`on_value`, `off_value`, or `dtype` are provided, `dtype` will default to the
+value `tf.float32`
+
+Note: If a non-numeric data type output is desired (tf.string, tf.bool, etc.),
+both `on_value` and `off_value` _must_ be provided to `one_hot`
Examples
=========
@@ -1515,6 +1529,22 @@ Then output is `[2 x 2 x 3]`:
]
```
+Using default values for `on_value` and `off_value`:
+
+```
+ indices = [0, 1, 2]
+ depth = 3
+```
+
+The output will be
+
+```
+ output =
+ [[1., 0., 0.],
+ [0., 1., 0.],
+ [0., 0., 1.]]
+```
+
##### Args:
@@ -1535,7 +1565,8 @@ Then output is `[2 x 2 x 3]`:
##### Raises:
-* <b>`TypeError`</b>: If dtype is `tf.string`
+* <b>`TypeError`</b>: If dtype of either `on_value` or `off_value` don't match `dtype`
+* <b>`TypeError`</b>: If dtype of `on_value` and `off_value` don't match one another
diff --git a/tensorflow/g3doc/api_docs/python/constant_op.md b/tensorflow/g3doc/api_docs/python/constant_op.md
index 1aaf39bd50b..008174f9d6f 100644
--- a/tensorflow/g3doc/api_docs/python/constant_op.md
+++ b/tensorflow/g3doc/api_docs/python/constant_op.md
@@ -60,7 +60,7 @@ tf.zeros_like(tensor) ==> [[0, 0, 0], [0, 0, 0]]
* <b>`tensor`</b>: A `Tensor`.
* <b>`dtype`</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
- `int8`, `int16`, `int32`, `int64`, `uint8`, `complex64`, or `complex128`.
+ `int8`, `int16`, `int32`, `int64`, `uint8`, or `complex64`.
* <b>`name`</b>: A name for the operation (optional).
@@ -119,7 +119,7 @@ tf.ones_like(tensor) ==> [[1, 1, 1], [1, 1, 1]]
* <b>`tensor`</b>: A `Tensor`.
* <b>`dtype`</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
- `int8`, `int16`, `int32`, `int64`, `uint8`, `complex64` or `complex128`.
+ `int8`, `int16`, `int32`, `int64`, `uint8`, or `complex64`.
* <b>`name`</b>: A name for the operation (optional).
diff --git a/tensorflow/g3doc/api_docs/python/contrib.learn.md b/tensorflow/g3doc/api_docs/python/contrib.learn.md
index 2bd7b7911f7..70aff96a846 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.learn.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.learn.md
@@ -3205,9 +3205,10 @@ and written to `output_dir`.
* <b>`output_dir`</b>: A string containing the directory to write a summary to.
* <b>`checkpoint_path`</b>: A string containing the path to a checkpoint to restore.
Can be `None` if the graph doesn't require loading any variables.
-* <b>`eval_dict`</b>: A `dict` mapping string names to tensors to evaluate for in every
- eval step.
-* <b>`update_op`</b>: A 'Tensor' which is run before evaluating 'eval_dict'.
+* <b>`eval_dict`</b>: A `dict` mapping string names to tensors to evaluate. It is
+ evaluated in every logging step. The result of the final evaluation is
+ returned. If update_op is None, then it's evaluated in every step.
+* <b>`update_op`</b>: A `Tensor` which is run in every step.
* <b>`global_step_tensor`</b>: A `Variable` containing the global step. If `None`,
one is extracted from the graph using the same logic as in `Supervisor`.
Used to place eval summaries on training curves.
@@ -3223,7 +3224,7 @@ and written to `output_dir`.
A tuple `(eval_results, global_step)`:
* <b>`eval_results`</b>: A `dict` mapping `string` to numeric values (`int`, `float`)
- that are the eval results from the last step of the eval. None if no
+ that are the result of running eval_dict in the last step. `None` if no
eval steps were run.
* <b>`global_step`</b>: The global step this evaluation corresponds to.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.contrib.learn.evaluate.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.contrib.learn.evaluate.md
index ef4679752a8..022662c3f6d 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.contrib.learn.evaluate.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.contrib.learn.evaluate.md
@@ -19,9 +19,10 @@ and written to `output_dir`.
* <b>`output_dir`</b>: A string containing the directory to write a summary to.
* <b>`checkpoint_path`</b>: A string containing the path to a checkpoint to restore.
Can be `None` if the graph doesn't require loading any variables.
-* <b>`eval_dict`</b>: A `dict` mapping string names to tensors to evaluate for in every
- eval step.
-* <b>`update_op`</b>: A 'Tensor' which is run before evaluating 'eval_dict'.
+* <b>`eval_dict`</b>: A `dict` mapping string names to tensors to evaluate. It is
+ evaluated in every logging step. The result of the final evaluation is
+ returned. If update_op is None, then it's evaluated in every step.
+* <b>`update_op`</b>: A `Tensor` which is run in every step.
* <b>`global_step_tensor`</b>: A `Variable` containing the global step. If `None`,
one is extracted from the graph using the same logic as in `Supervisor`.
Used to place eval summaries on training curves.
@@ -37,7 +38,7 @@ and written to `output_dir`.
A tuple `(eval_results, global_step)`:
* <b>`eval_results`</b>: A `dict` mapping `string` to numeric values (`int`, `float`)
- that are the eval results from the last step of the eval. None if no
+ that are the result of running eval_dict in the last step. `None` if no
eval steps were run.
* <b>`global_step`</b>: The global step this evaluation corresponds to.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.one_hot.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.one_hot.md
index 790ab80c8a0..eebb6ab643c 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.one_hot.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.one_hot.md
@@ -1,11 +1,18 @@
-### `tf.one_hot(indices, depth, on_value=1, off_value=0, axis=None, dtype=tf.float32, name=None)` {#one_hot}
+### `tf.one_hot(indices, depth, on_value=None, off_value=None, axis=None, dtype=None, name=None)` {#one_hot}
Returns a one-hot tensor.
The locations represented by indices in `indices` take value `on_value`,
-while all other locations take value `off_value`. By default, `on_value` is 1,
-and `off_value` is 0. The type of the output tensor is specified by `dtype`,
-which defaults to `tf.float32`.
+while all other locations take value `off_value`.
+
+`on_value` and `off_value` must have matching data types. If `dtype` is also
+provided, they must be the same data type as specified by `dtype`.
+
+If `on_value` is not provided, it will default to the value `1` with type
+`dtype`
+
+If `off_value` is not provided, it will default to the value `0` with type
+`dtype`
If the input `indices` is rank `N`, the output will have rank `N+1`. The
new axis is created at dimension `axis` (default: the new axis is appended
@@ -27,6 +34,13 @@ shape will be:
depth x batch x features if axis == 0
```
+If `dtype` is not provided, it will attempt to assume the data type of
+`on_value` or `off_value`, if one or both are passed in. If none of
+`on_value`, `off_value`, or `dtype` are provided, `dtype` will default to the
+value `tf.float32`
+
+Note: If a non-numeric data type output is desired (tf.string, tf.bool, etc.),
+both `on_value` and `off_value` _must_ be provided to `one_hot`
Examples
=========
@@ -74,6 +88,22 @@ Then output is `[2 x 2 x 3]`:
]
```
+Using default values for `on_value` and `off_value`:
+
+```
+ indices = [0, 1, 2]
+ depth = 3
+```
+
+The output will be
+
+```
+ output =
+ [[1., 0., 0.],
+ [0., 1., 0.],
+ [0., 0., 1.]]
+```
+
##### Args:
@@ -94,5 +124,6 @@ Then output is `[2 x 2 x 3]`:
##### Raises:
-* <b>`TypeError`</b>: If dtype is `tf.string`
+* <b>`TypeError`</b>: If dtype of either `on_value` or `off_value` don't match `dtype`
+* <b>`TypeError`</b>: If dtype of `on_value` and `off_value` don't match one another
diff --git a/tensorflow/g3doc/api_docs/python/nn.md b/tensorflow/g3doc/api_docs/python/nn.md
index 35a94808c1e..8254810db8a 100644
--- a/tensorflow/g3doc/api_docs/python/nn.md
+++ b/tensorflow/g3doc/api_docs/python/nn.md
@@ -163,7 +163,7 @@ case where both types are quantized.
* <b>`value`</b>: A `Tensor` with type `float`, `double`, `int64`, `int32`, `uint8`,
- `int16`, `int8`, `complex64` or `complex128`.
+ `int16`, `int8`, or `complex64`.
* <b>`bias`</b>: A 1-D `Tensor` with size matching the last dimension of `value`.
Must be the same type as `value` unless `value` is a quantized type,
in which case a different quantized type may be used.
@@ -186,7 +186,7 @@ Specifically, `y = 1 / (1 + exp(-x))`.
##### Args:
-* <b>`x`</b>: A Tensor with type `float`, `double`, `int32`, `complex64`, `complex128`, `int64`,
+* <b>`x`</b>: A Tensor with type `float`, `double`, `int32`, `complex64`, `int64`,
or `qint32`.
* <b>`name`</b>: A name for the operation (optional).
@@ -205,7 +205,7 @@ Computes hyperbolic tangent of `x` element-wise.
##### Args:
-* <b>`x`</b>: A Tensor with type `float`, `double`, `int32`, `complex64`, `complex128`, `int64`,
+* <b>`x`</b>: A Tensor with type `float`, `double`, `int32`, `complex64`, `int64`,
or `qint32`.
* <b>`name`</b>: A name for the operation (optional).