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-rw-r--r--tensorflow/core/api_def/base_api/api_def_ApplyAdaMax.pbtxt78
-rw-r--r--tensorflow/core/api_def/base_api/api_def_BroadcastTo.pbtxt41
-rw-r--r--tensorflow/core/api_def/base_api/api_def_ImageSummary.pbtxt2
-rw-r--r--tensorflow/core/api_def/base_api/api_def_ResourceApplyAdaMax.pbtxt72
-rw-r--r--tensorflow/core/api_def/base_api/api_def_StringStrip.pbtxt16
5 files changed, 208 insertions, 1 deletions
diff --git a/tensorflow/core/api_def/base_api/api_def_ApplyAdaMax.pbtxt b/tensorflow/core/api_def/base_api/api_def_ApplyAdaMax.pbtxt
new file mode 100644
index 0000000000..145d05de59
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ApplyAdaMax.pbtxt
@@ -0,0 +1,78 @@
+op {
+ graph_op_name: "ApplyAdaMax"
+ visibility: HIDDEN
+ in_arg {
+ name: "var"
+ description: <<END
+Should be from a Variable().
+END
+ }
+ in_arg {
+ name: "m"
+ description: <<END
+Should be from a Variable().
+END
+ }
+ in_arg {
+ name: "v"
+ description: <<END
+Should be from a Variable().
+END
+ }
+ in_arg {
+ name: "beta1_power"
+ description: <<END
+Must be a scalar.
+END
+ }
+ in_arg {
+ name: "lr"
+ description: <<END
+Scaling factor. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "beta1"
+ description: <<END
+Momentum factor. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "beta2"
+ description: <<END
+Momentum factor. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "epsilon"
+ description: <<END
+Ridge term. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "grad"
+ description: <<END
+The gradient.
+END
+ }
+ out_arg {
+ name: "out"
+ description: <<END
+Same as "var".
+END
+ }
+ attr {
+ name: "use_locking"
+ description: <<END
+If `True`, updating of the var, m, and v tensors will be protected
+by a lock; otherwise the behavior is undefined, but may exhibit less
+contention.
+END
+ }
+ summary: "Update \'*var\' according to the AdaMax algorithm."
+ description: <<END
+m_t <- beta1 * m_{t-1} + (1 - beta1) * g
+v_t <- max(beta2 * v_{t-1}, abs(g))
+variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon)
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_BroadcastTo.pbtxt b/tensorflow/core/api_def/base_api/api_def_BroadcastTo.pbtxt
new file mode 100644
index 0000000000..763760176a
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_BroadcastTo.pbtxt
@@ -0,0 +1,41 @@
+op {
+ graph_op_name: "BroadcastTo"
+ in_arg {
+ name: "input"
+ description: <<END
+A Tensor to broadcast.
+END
+ }
+ in_arg {
+ name: "shape"
+ description: <<END
+An 1-D `int` Tensor. The shape of the desired output.
+END
+ }
+ out_arg {
+ name: "output"
+ description: <<END
+A Tensor.
+END
+ }
+ summary: "Broadcast an array for a compatible shape."
+ description: <<END
+Broadcasting is the process of making arrays to have compatible shapes
+for arithmetic operations. Two shapes are compatible if for each
+dimension pair they are either equal or one of them is one. When trying
+to broadcast a Tensor to a shape, it starts with the trailing dimensions,
+and works its way forward.
+
+For example,
+```
+>>> x = tf.constant([1, 2, 3])
+>>> y = tf.broadcast_to(x, [3, 3])
+>>> sess.run(y)
+array([[1, 2, 3],
+ [1, 2, 3],
+ [1, 2, 3]], dtype=int32)
+```
+In the above example, the input Tensor with the shape of `[1, 3]`
+is broadcasted to output Tensor with shape of `[3, 3]`.
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ImageSummary.pbtxt b/tensorflow/core/api_def/base_api/api_def_ImageSummary.pbtxt
index 9b00f5b19d..56a3658fa0 100644
--- a/tensorflow/core/api_def/base_api/api_def_ImageSummary.pbtxt
+++ b/tensorflow/core/api_def/base_api/api_def_ImageSummary.pbtxt
@@ -61,7 +61,7 @@ build the `tag` of the summary values:
generated sequentially as '*tag*/image/0', '*tag*/image/1', etc.
The `bad_color` argument is the color to use in the generated images for
-non-finite input values. It is a `unit8` 1-D tensor of length `channels`.
+non-finite input values. It is a `uint8` 1-D tensor of length `channels`.
Each element must be in the range `[0, 255]` (It represents the value of a
pixel in the output image). Non-finite values in the input tensor are
replaced by this tensor in the output image. The default value is the color
diff --git a/tensorflow/core/api_def/base_api/api_def_ResourceApplyAdaMax.pbtxt b/tensorflow/core/api_def/base_api/api_def_ResourceApplyAdaMax.pbtxt
new file mode 100644
index 0000000000..a3f2188ba5
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ResourceApplyAdaMax.pbtxt
@@ -0,0 +1,72 @@
+op {
+ graph_op_name: "ResourceApplyAdaMax"
+ visibility: HIDDEN
+ in_arg {
+ name: "var"
+ description: <<END
+Should be from a Variable().
+END
+ }
+ in_arg {
+ name: "m"
+ description: <<END
+Should be from a Variable().
+END
+ }
+ in_arg {
+ name: "v"
+ description: <<END
+Should be from a Variable().
+END
+ }
+ in_arg {
+ name: "beta1_power"
+ description: <<END
+Must be a scalar.
+END
+ }
+ in_arg {
+ name: "lr"
+ description: <<END
+Scaling factor. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "beta1"
+ description: <<END
+Momentum factor. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "beta2"
+ description: <<END
+Momentum factor. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "epsilon"
+ description: <<END
+Ridge term. Must be a scalar.
+END
+ }
+ in_arg {
+ name: "grad"
+ description: <<END
+The gradient.
+END
+ }
+ attr {
+ name: "use_locking"
+ description: <<END
+If `True`, updating of the var, m, and v tensors will be protected
+by a lock; otherwise the behavior is undefined, but may exhibit less
+contention.
+END
+ }
+ summary: "Update \'*var\' according to the AdaMax algorithm."
+ description: <<END
+m_t <- beta1 * m_{t-1} + (1 - beta1) * g
+v_t <- max(beta2 * v_{t-1}, abs(g))
+variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon)
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_StringStrip.pbtxt b/tensorflow/core/api_def/base_api/api_def_StringStrip.pbtxt
new file mode 100644
index 0000000000..12fbdfdf3f
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_StringStrip.pbtxt
@@ -0,0 +1,16 @@
+op {
+ graph_op_name: "StringStrip"
+ in_arg {
+ name: "input"
+ description: <<END
+A string `Tensor` of any shape.
+END
+ }
+ out_arg {
+ name: "output"
+ description: <<END
+A string `Tensor` of the same shape as the input.
+END
+ }
+ summary: "Strip leading and trailing whitespaces from the Tensor."
+}