From fbc8574ac64ae72f35f415baddfd25dff55163e1 Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Thu, 1 Dec 2016 15:53:03 -0800 Subject: Update generated Python Op docs. Change: 140789077 --- .../shard0/tf.SparseTensorValue.md | 26 ++++--- .../functions_and_classes/shard0/tf.TensorArray.md | 7 +- .../shard2/tf.SparseTensorValue.__new__.md | 4 - .../shard3/tf.SparseTensor.md | 60 +++++++++------ tensorflow/g3doc/api_docs/python/index.md | 1 - tensorflow/g3doc/api_docs/python/sparse_ops.md | 86 +++++++++++++--------- .../g3doc/api_docs/python/tensor_array_ops.md | 7 +- 7 files changed, 114 insertions(+), 77 deletions(-) delete mode 100644 tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.SparseTensorValue.__new__.md diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md index ad46827ac2..118158d490 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md @@ -1,50 +1,52 @@ -SparseTensorValue(indices, values, shape) +Stores the calculated numpy arrays representing a `SparseTensor`. + +Returned as the output of a session.run on a `SparseTensor` object. - - - -#### `tf.SparseTensorValue.__getnewargs__()` {#SparseTensorValue.__getnewargs__} +#### `tf.SparseTensorValue.__getitem__(i)` {#SparseTensorValue.__getitem__} + -Return self as a plain tuple. Used by copy and pickle. - - - -#### `tf.SparseTensorValue.__getstate__()` {#SparseTensorValue.__getstate__} +#### `tf.SparseTensorValue.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensorValue.__init__} + -Exclude the OrderedDict from pickling - - - -#### `tf.SparseTensorValue.__new__(_cls, indices, values, shape)` {#SparseTensorValue.__new__} +#### `tf.SparseTensorValue.__iter__()` {#SparseTensorValue.__iter__} + -Create new instance of SparseTensorValue(indices, values, shape) - - - -#### `tf.SparseTensorValue.__repr__()` {#SparseTensorValue.__repr__} +#### `tf.SparseTensorValue.dense_shape` {#SparseTensorValue.dense_shape} + -Return a nicely formatted representation string - - - #### `tf.SparseTensorValue.indices` {#SparseTensorValue.indices} -Alias for field number 0 + - - - #### `tf.SparseTensorValue.shape` {#SparseTensorValue.shape} -Alias for field number 2 + - - - #### `tf.SparseTensorValue.values` {#SparseTensorValue.values} -Alias for field number 1 + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md index 97fb6b760c..a0252d096a 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md @@ -208,7 +208,7 @@ Split the values of a `Tensor` into the TensorArray. #### Other Methods - - - -#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, elem_shape=None, name=None)` {#TensorArray.__init__} +#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, element_shape=None, name=None)` {#TensorArray.__init__} Construct a new TensorArray or wrap an existing TensorArray handle. @@ -239,8 +239,9 @@ is created within a `while_loop`. `TensorArray.flow`. * `infer_shape`: (optional, default: True) If True, shape inference is enabled. In this case, all elements must have the same shape. -* `elem_shape`: (optional, default: None) A TensorShape object specifying - the shape of all the elements of the TensorArray. +* `element_shape`: (optional, default: None) A `TensorShape` object specifying + the shape constraints of each of the elements of the TensorArray. + Need not be fully defined. * `name`: A name for the operation (optional). ##### Raises: diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.SparseTensorValue.__new__.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.SparseTensorValue.__new__.md deleted file mode 100644 index e805f29b98..0000000000 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.SparseTensorValue.__new__.md +++ /dev/null @@ -1,4 +0,0 @@ -#### `tf.SparseTensorValue.__new__(_cls, indices, values, shape)` {#SparseTensorValue.__new__} - -Create new instance of SparseTensorValue(indices, values, shape) - diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md index d89b4e70c4..137cf621d4 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md @@ -1,37 +1,41 @@ Represents a sparse tensor. TensorFlow represents a sparse tensor as three separate dense tensors: -`indices`, `values`, and `shape`. In Python, the three tensors are +`indices`, `values`, and `dense_shape`. In Python, the three tensors are collected into a `SparseTensor` class for ease of use. If you have separate -`indices`, `values`, and `shape` tensors, wrap them in a `SparseTensor` +`indices`, `values`, and `dense_shape` tensors, wrap them in a `SparseTensor` object before passing to the ops below. -Concretely, the sparse tensor `SparseTensor(indices, values, shape)` +Concretely, the sparse tensor `SparseTensor(indices, values, dense_shape)` comprises the following components, where `N` and `ndims` are the number of values and number of dimensions in the `SparseTensor`, respectively: -* `indices`: A 2-D int64 tensor of shape `[N, ndims]`, which specifies +* `indices`: A 2-D int64 tensor of dense_shape `[N, ndims]`, which specifies the indices of the elements in the sparse tensor that contain nonzero values (elements are zero-indexed). For example, `indices=[[1,3], [2,4]]` specifies that the elements with indexes of [1,3] and [2,4] have nonzero values. -* `values`: A 1-D tensor of any type and shape `[N]`, which supplies the +* `values`: A 1-D tensor of any type and dense_shape `[N]`, which supplies the values for each element in `indices`. For example, given `indices=[[1,3], [2,4]]`, the parameter `values=[18, 3.6]` specifies that element [1,3] of the sparse tensor has a value of 18, and element [2,4] of the tensor has a value of 3.6. -* `shape`: A 1-D int64 tensor of shape `[ndims]`, which specifies the shape - of the sparse tensor. Takes a list indicating the number of elements in - each dimension. For example, `shape=[3,6]` specifies a two-dimensional 3x6 - tensor, `shape=[2,3,4]` specifies a three-dimensional 2x3x4 tensor, and - `shape=[9]` specifies a one-dimensional tensor with 9 elements. +* `dense_shape`: A 1-D int64 tensor of dense_shape `[ndims]`, which specifies +the + dense_shape of the sparse tensor. Takes a list indicating the number of + elements + in each dimension. For example, `dense_shape=[3,6]` specifies a + two-dimensional + 3x6 tensor, `dense_shape=[2,3,4]` specifies a three-dimensional 2x3x4 + tensor, and + `dense_shape=[9]` specifies a one-dimensional tensor with 9 elements. The corresponding dense tensor satisfies: ```python -dense.shape = shape +dense.shape = dense_shape dense[tuple(indices[i])] = values[i] ``` @@ -44,7 +48,7 @@ obtained by calling `tf.sparse_reorder(st)`. Example: The sparse tensor ```python -SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], shape=[3, 4]) +SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4]) ``` represents the dense tensor @@ -57,27 +61,34 @@ represents the dense tensor - - - -#### `tf.SparseTensor.__init__(indices, values, shape)` {#SparseTensor.__init__} +#### `tf.SparseTensor.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensor.__init__} Creates a `SparseTensor`. ##### Args: -* `indices`: A 2-D int64 tensor of shape `[N, ndims]`. -* `values`: A 1-D tensor of any type and shape `[N]`. -* `shape`: A 1-D int64 tensor of shape `[ndims]`. +* `indices`: A 2-D int64 tensor of dense_shape `[N, ndims]`. +* `values`: A 1-D tensor of any type and dense_shape `[N]`. +* `dense_shape`: A 1-D int64 tensor of dense_shape `[ndims]`. +* `shape`: Temporary. Legacy naming of dense_shape. Only one of `shape` or + `dense_shape` must be provided. ##### Returns: - A `SparseTensor` + A `SparseTensor`. + +##### Raises: + + +* `ValueError`: if both `shape` and `dense_shape` are provided. - - - #### `tf.SparseTensor.get_shape()` {#SparseTensor.get_shape} -Get the `TensorShape` that represents the shape of the dense tensor. +Get the `TensorShape` representing the shape of the dense tensor. ##### Returns: @@ -92,7 +103,7 @@ The indices of non-zero values in the represented dense tensor. ##### Returns: - A 2-D Tensor of int64 with shape `[N, ndims]`, where `N` is the + A 2-D Tensor of int64 with dense_shape `[N, ndims]`, where `N` is the number of non-zero values in the tensor, and `ndims` is the rank. @@ -109,7 +120,7 @@ The non-zero values in the represented dense tensor. - - - -#### `tf.SparseTensor.shape` {#SparseTensor.shape} +#### `tf.SparseTensor.dense_shape` {#SparseTensor.dense_shape} A 1-D Tensor of int64 representing the shape of the dense tensor. @@ -132,7 +143,7 @@ The `Operation` that produces `values` as an output. #### `tf.SparseTensor.graph` {#SparseTensor.graph} -The `Graph` that contains the index, value, and shape tensors. +The `Graph` that contains the index, value, and dense_shape tensors. @@ -248,3 +259,10 @@ available, or `session` must be specified explicitly. +- - - + +#### `tf.SparseTensor.shape` {#SparseTensor.shape} + +Legacy property returning `dense_shape`. + + diff --git a/tensorflow/g3doc/api_docs/python/index.md b/tensorflow/g3doc/api_docs/python/index.md index ae1f47ec43..5c04276e93 100644 --- a/tensorflow/g3doc/api_docs/python/index.md +++ b/tensorflow/g3doc/api_docs/python/index.md @@ -415,7 +415,6 @@ * [`transpose_image`](../../api_docs/python/image.md#transpose_image) * **[Sparse Tensors](../../api_docs/python/sparse_ops.md)**: - * [`shape`](../../api_docs/python/sparse_ops.md#shape) * [`sparse_add`](../../api_docs/python/sparse_ops.md#sparse_add) * [`sparse_concat`](../../api_docs/python/sparse_ops.md#sparse_concat) * [`sparse_fill_empty_rows`](../../api_docs/python/sparse_ops.md#sparse_fill_empty_rows) diff --git a/tensorflow/g3doc/api_docs/python/sparse_ops.md b/tensorflow/g3doc/api_docs/python/sparse_ops.md index 433a5cd4eb..35611e117c 100644 --- a/tensorflow/g3doc/api_docs/python/sparse_ops.md +++ b/tensorflow/g3doc/api_docs/python/sparse_ops.md @@ -21,37 +21,41 @@ dimension, and dense along all other dimensions. Represents a sparse tensor. TensorFlow represents a sparse tensor as three separate dense tensors: -`indices`, `values`, and `shape`. In Python, the three tensors are +`indices`, `values`, and `dense_shape`. In Python, the three tensors are collected into a `SparseTensor` class for ease of use. If you have separate -`indices`, `values`, and `shape` tensors, wrap them in a `SparseTensor` +`indices`, `values`, and `dense_shape` tensors, wrap them in a `SparseTensor` object before passing to the ops below. -Concretely, the sparse tensor `SparseTensor(indices, values, shape)` +Concretely, the sparse tensor `SparseTensor(indices, values, dense_shape)` comprises the following components, where `N` and `ndims` are the number of values and number of dimensions in the `SparseTensor`, respectively: -* `indices`: A 2-D int64 tensor of shape `[N, ndims]`, which specifies +* `indices`: A 2-D int64 tensor of dense_shape `[N, ndims]`, which specifies the indices of the elements in the sparse tensor that contain nonzero values (elements are zero-indexed). For example, `indices=[[1,3], [2,4]]` specifies that the elements with indexes of [1,3] and [2,4] have nonzero values. -* `values`: A 1-D tensor of any type and shape `[N]`, which supplies the +* `values`: A 1-D tensor of any type and dense_shape `[N]`, which supplies the values for each element in `indices`. For example, given `indices=[[1,3], [2,4]]`, the parameter `values=[18, 3.6]` specifies that element [1,3] of the sparse tensor has a value of 18, and element [2,4] of the tensor has a value of 3.6. -* `shape`: A 1-D int64 tensor of shape `[ndims]`, which specifies the shape - of the sparse tensor. Takes a list indicating the number of elements in - each dimension. For example, `shape=[3,6]` specifies a two-dimensional 3x6 - tensor, `shape=[2,3,4]` specifies a three-dimensional 2x3x4 tensor, and - `shape=[9]` specifies a one-dimensional tensor with 9 elements. +* `dense_shape`: A 1-D int64 tensor of dense_shape `[ndims]`, which specifies +the + dense_shape of the sparse tensor. Takes a list indicating the number of + elements + in each dimension. For example, `dense_shape=[3,6]` specifies a + two-dimensional + 3x6 tensor, `dense_shape=[2,3,4]` specifies a three-dimensional 2x3x4 + tensor, and + `dense_shape=[9]` specifies a one-dimensional tensor with 9 elements. The corresponding dense tensor satisfies: ```python -dense.shape = shape +dense.shape = dense_shape dense[tuple(indices[i])] = values[i] ``` @@ -64,7 +68,7 @@ obtained by calling `tf.sparse_reorder(st)`. Example: The sparse tensor ```python -SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], shape=[3, 4]) +SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4]) ``` represents the dense tensor @@ -77,27 +81,34 @@ represents the dense tensor - - - -#### `tf.SparseTensor.__init__(indices, values, shape)` {#SparseTensor.__init__} +#### `tf.SparseTensor.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensor.__init__} Creates a `SparseTensor`. ##### Args: -* `indices`: A 2-D int64 tensor of shape `[N, ndims]`. -* `values`: A 1-D tensor of any type and shape `[N]`. -* `shape`: A 1-D int64 tensor of shape `[ndims]`. +* `indices`: A 2-D int64 tensor of dense_shape `[N, ndims]`. +* `values`: A 1-D tensor of any type and dense_shape `[N]`. +* `dense_shape`: A 1-D int64 tensor of dense_shape `[ndims]`. +* `shape`: Temporary. Legacy naming of dense_shape. Only one of `shape` or + `dense_shape` must be provided. ##### Returns: - A `SparseTensor` + A `SparseTensor`. + +##### Raises: + + +* `ValueError`: if both `shape` and `dense_shape` are provided. - - - #### `tf.SparseTensor.get_shape()` {#SparseTensor.get_shape} -Get the `TensorShape` that represents the shape of the dense tensor. +Get the `TensorShape` representing the shape of the dense tensor. ##### Returns: @@ -112,7 +123,7 @@ The indices of non-zero values in the represented dense tensor. ##### Returns: - A 2-D Tensor of int64 with shape `[N, ndims]`, where `N` is the + A 2-D Tensor of int64 with dense_shape `[N, ndims]`, where `N` is the number of non-zero values in the tensor, and `ndims` is the rank. @@ -129,7 +140,7 @@ The non-zero values in the represented dense tensor. - - - -#### `tf.SparseTensor.shape` {#SparseTensor.shape} +#### `tf.SparseTensor.dense_shape` {#SparseTensor.dense_shape} A 1-D Tensor of int64 representing the shape of the dense tensor. @@ -152,7 +163,7 @@ The `Operation` that produces `values` as an output. #### `tf.SparseTensor.graph` {#SparseTensor.graph} -The `Graph` that contains the index, value, and shape tensors. +The `Graph` that contains the index, value, and dense_shape tensors. @@ -268,59 +279,68 @@ available, or `session` must be specified explicitly. +- - - + +#### `tf.SparseTensor.shape` {#SparseTensor.shape} + +Legacy property returning `dense_shape`. + + - - - ### `class tf.SparseTensorValue` {#SparseTensorValue} -SparseTensorValue(indices, values, shape) +Stores the calculated numpy arrays representing a `SparseTensor`. + +Returned as the output of a session.run on a `SparseTensor` object. - - - -#### `tf.SparseTensorValue.__getnewargs__()` {#SparseTensorValue.__getnewargs__} +#### `tf.SparseTensorValue.__getitem__(i)` {#SparseTensorValue.__getitem__} + -Return self as a plain tuple. Used by copy and pickle. - - - -#### `tf.SparseTensorValue.__getstate__()` {#SparseTensorValue.__getstate__} +#### `tf.SparseTensorValue.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensorValue.__init__} + -Exclude the OrderedDict from pickling - - - -#### `tf.SparseTensorValue.__new__(_cls, indices, values, shape)` {#SparseTensorValue.__new__} +#### `tf.SparseTensorValue.__iter__()` {#SparseTensorValue.__iter__} + -Create new instance of SparseTensorValue(indices, values, shape) - - - -#### `tf.SparseTensorValue.__repr__()` {#SparseTensorValue.__repr__} +#### `tf.SparseTensorValue.dense_shape` {#SparseTensorValue.dense_shape} + -Return a nicely formatted representation string - - - #### `tf.SparseTensorValue.indices` {#SparseTensorValue.indices} -Alias for field number 0 + - - - #### `tf.SparseTensorValue.shape` {#SparseTensorValue.shape} -Alias for field number 2 + - - - #### `tf.SparseTensorValue.values` {#SparseTensorValue.values} -Alias for field number 1 + diff --git a/tensorflow/g3doc/api_docs/python/tensor_array_ops.md b/tensorflow/g3doc/api_docs/python/tensor_array_ops.md index 61927d4694..c5019f41bf 100644 --- a/tensorflow/g3doc/api_docs/python/tensor_array_ops.md +++ b/tensorflow/g3doc/api_docs/python/tensor_array_ops.md @@ -225,7 +225,7 @@ Split the values of a `Tensor` into the TensorArray. #### Other Methods - - - -#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, elem_shape=None, name=None)` {#TensorArray.__init__} +#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, element_shape=None, name=None)` {#TensorArray.__init__} Construct a new TensorArray or wrap an existing TensorArray handle. @@ -256,8 +256,9 @@ is created within a `while_loop`. `TensorArray.flow`. * `infer_shape`: (optional, default: True) If True, shape inference is enabled. In this case, all elements must have the same shape. -* `elem_shape`: (optional, default: None) A TensorShape object specifying - the shape of all the elements of the TensorArray. +* `element_shape`: (optional, default: None) A `TensorShape` object specifying + the shape constraints of each of the elements of the TensorArray. + Need not be fully defined. * `name`: A name for the operation (optional). ##### Raises: -- cgit v1.2.3