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Update ops-related pbtxt files.

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Change: 120387174
This commit is contained in:
A. Unique TensorFlower 2016-04-20 15:07:18 -08:00 committed by TensorFlower Gardener
parent 30334d28c0
commit f0ff08685a
2 changed files with 318 additions and 0 deletions
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294
tensorflow/core/ops/compat/ops_history.v0.pbtxt
View File

@ -383,6 +383,47 @@ op {
}
}
}
op {
name: "AdjustContrast"
input_arg {
name: "images"
type_attr: "T"
}
input_arg {
name: "contrast_factor"
type: DT_FLOAT
}
input_arg {
name: "min_value"
type: DT_FLOAT
}
input_arg {
name: "max_value"
type: DT_FLOAT
}
output_arg {
name: "output"
type: DT_FLOAT
}
attr {
name: "T"
type: "type"
allowed_values {
list {
type: DT_UINT8
type: DT_INT8
type: DT_INT16
type: DT_INT32
type: DT_INT64
type: DT_FLOAT
type: DT_DOUBLE
}
}
}
deprecation {
version: 2
}
}
op {
name: "AdjustContrastv2"
input_arg {
@ -3656,6 +3697,66 @@ op {
type: "bool"
}
}
op {
name: "BatchNormWithGlobalNormalization"
input_arg {
name: "t"
type_attr: "T"
}
input_arg {
name: "m"
type_attr: "T"
}
input_arg {
name: "v"
type_attr: "T"
}
input_arg {
name: "beta"
type_attr: "T"
}
input_arg {
name: "gamma"
type_attr: "T"
}
output_arg {
name: "result"
type_attr: "T"
}
attr {
name: "T"
type: "type"
allowed_values {
list {
type: DT_FLOAT
type: DT_DOUBLE
type: DT_INT64
type: DT_INT32
type: DT_UINT8
type: DT_UINT16
type: DT_INT16
type: DT_INT8
type: DT_COMPLEX64
type: DT_COMPLEX128
type: DT_QINT8
type: DT_QUINT8
type: DT_QINT32
type: DT_HALF
}
}
}
attr {
name: "variance_epsilon"
type: "float"
}
attr {
name: "scale_after_normalization"
type: "bool"
}
deprecation {
version: 9
}
}
op {
name: "BatchNormWithGlobalNormalizationGrad"
input_arg {
@ -3942,6 +4043,82 @@ op {
type: "bool"
}
}
op {
name: "BatchNormWithGlobalNormalizationGrad"
input_arg {
name: "t"
type_attr: "T"
}
input_arg {
name: "m"
type_attr: "T"
}
input_arg {
name: "v"
type_attr: "T"
}
input_arg {
name: "gamma"
type_attr: "T"
}
input_arg {
name: "backprop"
type_attr: "T"
}
output_arg {
name: "dx"
type_attr: "T"
}
output_arg {
name: "dm"
type_attr: "T"
}
output_arg {
name: "dv"
type_attr: "T"
}
output_arg {
name: "db"
type_attr: "T"
}
output_arg {
name: "dg"
type_attr: "T"
}
attr {
name: "T"
type: "type"
allowed_values {
list {
type: DT_FLOAT
type: DT_DOUBLE
type: DT_INT64
type: DT_INT32
type: DT_UINT8
type: DT_UINT16
type: DT_INT16
type: DT_INT8
type: DT_COMPLEX64
type: DT_COMPLEX128
type: DT_QINT8
type: DT_QUINT8
type: DT_QINT32
type: DT_HALF
}
}
}
attr {
name: "variance_epsilon"
type: "float"
}
attr {
name: "scale_after_normalization"
type: "bool"
}
deprecation {
version: 9
}
}
op {
name: "BatchSelfAdjointEig"
input_arg {
@ -11855,6 +12032,54 @@ op {
}
is_stateful: true
}
op {
name: "RandomCrop"
input_arg {
name: "image"
type_attr: "T"
}
input_arg {
name: "size"
type: DT_INT64
}
output_arg {
name: "output"
type_attr: "T"
}
attr {
name: "T"
type: "type"
allowed_values {
list {
type: DT_UINT8
type: DT_INT8
type: DT_INT16
type: DT_INT32
type: DT_INT64
type: DT_FLOAT
type: DT_DOUBLE
}
}
}
attr {
name: "seed"
type: "int"
default_value {
i: 0
}
}
attr {
name: "seed2"
type: "int"
default_value {
i: 0
}
}
deprecation {
version: 8
}
is_stateful: true
}
op {
name: "RandomShuffle"
input_arg {
@ -18823,6 +19048,28 @@ op {
type: "type"
}
}
op {
name: "TileGrad"
input_arg {
name: "input"
type_attr: "T"
}
input_arg {
name: "multiples"
type: DT_INT32
}
output_arg {
name: "output"
type_attr: "T"
}
attr {
name: "T"
type: "type"
}
deprecation {
version: 3
}
}
op {
name: "TopK"
input_arg {
@ -19031,6 +19278,53 @@ op {
}
}
}
op {
name: "TopK"
input_arg {
name: "input"
type_attr: "T"
}
output_arg {
name: "values"
type_attr: "T"
}
output_arg {
name: "indices"
type: DT_INT32
}
attr {
name: "k"
type: "int"
has_minimum: true
}
attr {
name: "sorted"
type: "bool"
default_value {
b: true
}
}
attr {
name: "T"
type: "type"
allowed_values {
list {
type: DT_FLOAT
type: DT_DOUBLE
type: DT_INT32
type: DT_INT64
type: DT_UINT8
type: DT_INT16
type: DT_INT8
type: DT_UINT16
type: DT_HALF
}
}
}
deprecation {
version: 7
}
}
op {
name: "TopKV2"
input_arg {

24
tensorflow/core/ops/ops.pbtxt
View File

@ -154,6 +154,10 @@ op {
}
}
summary: "Deprecated. Disallowed in GraphDef version >= 2."
deprecation {
version: 2
explanation: "Use AdjustContrastv2 instead"
}
}
op {
name: "AdjustContrastv2"
@ -1681,6 +1685,10 @@ op {
}
summary: "Batch normalization."
description: "This op is deprecated. Prefer `tf.nn.batch_normalization`."
deprecation {
version: 9
explanation: "Use tf.nn.batch_normalization()"
}
}
op {
name: "BatchNormWithGlobalNormalizationGrad"
@ -1768,6 +1776,10 @@ op {
}
summary: "Gradients for batch normalization."
description: "This op is deprecated. See `tf.nn.batch_normalization`."
deprecation {
version: 9
explanation: "Use tf.nn.batch_normalization()"
}
}
op {
name: "BatchSelfAdjointEig"
@ -7370,6 +7382,10 @@ op {
}
summary: "Randomly crop `image`."
description: "`size` is a 1-D int64 tensor with 2 elements representing the crop height and\nwidth. The values must be non negative.\n\nThis Op picks a random location in `image` and crops a `height` by `width`\nrectangle from that location. The random location is picked so the cropped\narea will fit inside the original image."
deprecation {
version: 8
explanation: "Random crop is now pure Python"
}
is_stateful: true
}
op {
@ -11925,6 +11941,10 @@ op {
}
summary: "Returns the gradient of `Tile`."
description: "Since `Tile` takes an input and repeats the input `multiples` times\nalong each dimension, `TileGrad` takes in `multiples` and aggregates\neach repeated tile of `input` into `output`."
deprecation {
version: 3
explanation: "TileGrad has been replaced with reduce_sum"
}
}
op {
name: "TopK"
@ -11976,6 +11996,10 @@ op {
}
summary: "Finds values and indices of the `k` largest elements for the last dimension."
description: "If the input is a vector (rank-1), finds the `k` largest entries in the vector\nand outputs their values and indices as vectors. Thus `values[j]` is the\n`j`-th largest entry in `input`, and its index is `indices[j]`.\n\nFor matrices (resp. higher rank input), computes the top `k` entries in each\nrow (resp. vector along the last dimension). Thus,\n\n values.shape = indices.shape = input.shape[:-1] + [k]\n\nIf two elements are equal, the lower-index element appears first.\n\nIf `k` varies dynamically, use `TopKV2` below."
deprecation {
version: 7
explanation: "Use TopKV2 instead"
}
}
op {
name: "TopKV2"