From aab03a055d314977cd95c0a277e3dc3d2f23b2a1 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Wed, 15 Jun 2016 15:04:39 -0800
Subject: [PATCH] Update ops-related pbtxt files. Change: 125003491

---
 .../core/ops/compat/ops_history.v0.pbtxt      | 57 +++++++++++++++++
 tensorflow/core/ops/ops.pbtxt                 | 64 +++++++++++++++++++
 2 files changed, 121 insertions(+)

diff --git a/tensorflow/core/ops/compat/ops_history.v0.pbtxt b/tensorflow/core/ops/compat/ops_history.v0.pbtxt
index 191b261ab63..ca3634f7f79 100644
--- a/tensorflow/core/ops/compat/ops_history.v0.pbtxt
+++ b/tensorflow/core/ops/compat/ops_history.v0.pbtxt
@@ -23067,6 +23067,63 @@ op {
     type: "type"
   }
 }
+op {
+  name: "StridedSlice"
+  input_arg {
+    name: "input"
+    type_attr: "T"
+  }
+  input_arg {
+    name: "begin"
+    type_attr: "Index"
+  }
+  input_arg {
+    name: "end"
+    type_attr: "Index"
+  }
+  input_arg {
+    name: "strides"
+    type_attr: "Index"
+  }
+  output_arg {
+    name: "output"
+    type_attr: "T"
+  }
+  attr {
+    name: "T"
+    type: "type"
+  }
+  attr {
+    name: "Index"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_INT32
+        type: DT_INT64
+      }
+    }
+  }
+  attr {
+    name: "begin_mask"
+    type: "int"
+  }
+  attr {
+    name: "end_mask"
+    type: "int"
+  }
+  attr {
+    name: "ellipse_mask"
+    type: "int"
+  }
+  attr {
+    name: "new_axis_mask"
+    type: "int"
+  }
+  attr {
+    name: "shrink_axis_mask"
+    type: "int"
+  }
+}
 op {
   name: "StringToHashBucket"
   input_arg {
diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt
index a63ea49cd02..33770845f93 100644
--- a/tensorflow/core/ops/ops.pbtxt
+++ b/tensorflow/core/ops/ops.pbtxt
@@ -13376,6 +13376,70 @@ op {
   summary: "Stops gradient computation."
   description: "When executed in a graph, this op outputs its input tensor as-is.\n\nWhen building ops to compute gradients, this op prevents the contribution of\nits inputs to be taken into account.  Normally, the gradient generator adds ops\nto a graph to compute the derivatives of a specified \'loss\' by recursively\nfinding out inputs that contributed to its computation.  If you insert this op\nin the graph it inputs are masked from the gradient generator.  They are not\ntaken into account for computing gradients.\n\nThis is useful any time you want to compute a value with TensorFlow but need\nto pretend that the value was a constant. Some examples include:\n\n*  The *EM* algorithm where the *M-step* should not involve backpropagation\n   through the output of the *E-step*.\n*  Contrastive divergence training of Boltzmann machines where, when\n   differentiating the energy function, the training must not backpropagate\n   through the graph that generated the samples from the model.\n*  Adversarial training, where no backprop should happen through the adversarial\n   example generation process."
 }
+op {
+  name: "StridedSlice"
+  input_arg {
+    name: "input"
+    type_attr: "T"
+  }
+  input_arg {
+    name: "begin"
+    description: "`begin[i]` specifies the offset into the `i`th dimension of\n`input` to slice from."
+    type_attr: "Index"
+  }
+  input_arg {
+    name: "end"
+    description: "`end[i]` specifies the first offset into the `i`th dimension of\n`input` that will not be extracted. Out or range values are\nclamped to `[0,dim[i]) if slice[i] > 0` or `[-1,dim[i]-1]`\n`if slice[i] < 0`"
+    type_attr: "Index"
+  }
+  input_arg {
+    name: "strides"
+    description: "`strides[i]` specifies the increment in the `i`th dimension\nafter extracting a given element. Negative indices will reverse\nthe original order. Out or range values are\nclamped to `[0,dim[i]) if slice[i]>0` or `[-1,dim[i]-1] if slice[i] < 0`"
+    type_attr: "Index"
+  }
+  output_arg {
+    name: "output"
+    type_attr: "T"
+  }
+  attr {
+    name: "T"
+    type: "type"
+  }
+  attr {
+    name: "Index"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_INT32
+        type: DT_INT64
+      }
+    }
+  }
+  attr {
+    name: "begin_mask"
+    type: "int"
+    description: "a bitmask where a bit i being 1 means to ignore the begin\nvalue and instead use the largest interval possible. At runtime\nbegin[i] will be replaced with `[0, n-1) if `stride[i] > 0` or\n`[-1, n-1]` if `stride[i] < 0`"
+  }
+  attr {
+    name: "end_mask"
+    type: "int"
+    description: "analogous to `begin_mask`"
+  }
+  attr {
+    name: "ellipse_mask"
+    type: "int"
+  }
+  attr {
+    name: "new_axis_mask"
+    type: "int"
+  }
+  attr {
+    name: "shrink_axis_mask"
+    type: "int"
+  }
+  summary: "Return a strided slice from `input`."
+  description: "The output tensor is a tensor with dimensions implied by `begin`,\n`end`, and `strides`, whose values are extracted from `begin`.\n\nSpecifically, the result tensor at index `(i[0], i[1], ..., i[n-1])`\nwill obtain the value `input[begin[0] + i[0] * stride[0], ..., `\n                            `begin[n-1] + i[n-1] * stride[n-1])]`.\n\n*Requirements*:\n  `0 != strides[i] for i in [0, n)`"
+}
 op {
   name: "StringToHashBucket"
   input_arg {