From 97011c17de3f21ae7d40f89f09bf7513dc0e49aa Mon Sep 17 00:00:00 2001
From: Geoffrey Irving <irving@naml.us>
Date: Fri, 7 Sep 2018 09:01:56 -0700
Subject: [PATCH] Make tf.random_uniform([0], maxval=0, dtype=tf.int32) not
 crash

For integers, tf.random_uniform enforces a nonempty range with minval < maxval.
However, an empty range is fine if we're producing no output values, and
this degenerate case occurs naturally for some code patterns.

Thus, tf.random_uniform now allows empty ranges for integer random
numbers if the output shape is empty.
---
 tensorflow/core/kernels/random_op.cc                   | 10 +++++++---
 .../python/kernel_tests/random/random_ops_test.py      |  9 +++++++++
 2 files changed, 16 insertions(+), 3 deletions(-)

diff --git a/tensorflow/core/kernels/random_op.cc b/tensorflow/core/kernels/random_op.cc
index e37232539f2..04a53697c09 100644
--- a/tensorflow/core/kernels/random_op.cc
+++ b/tensorflow/core/kernels/random_op.cc
@@ -231,7 +231,13 @@ class RandomUniformIntOp : public OpKernel {
                 errors::InvalidArgument("maxval must be 0-D, got shape ",
                                         maxval.shape().DebugString()));
 
-    // Verify that minval < maxval
+    // Allocate output, and exit early if possible
+    Tensor* output;
+    OP_REQUIRES_OK(ctx, AllocateOutputWithShape(ctx, shape, 0, &output));
+    if (output->NumElements() == 0) return;
+
+    // Verify that minval < maxval.  This check intentionally happens after the
+    // early exit for empty output.  Zero impossible things are fine.
     IntType lo = minval.scalar<IntType>()();
     IntType hi = maxval.scalar<IntType>()();
     OP_REQUIRES(
@@ -243,8 +249,6 @@ class RandomUniformIntOp : public OpKernel {
         Distribution;
     Distribution dist(lo, hi);
 
-    Tensor* output;
-    OP_REQUIRES_OK(ctx, AllocateOutputWithShape(ctx, shape, 0, &output));
     auto output_flat = output->flat<IntType>();
     functor::FillPhiloxRandom<Device, Distribution>()(
         ctx, ctx->eigen_device<Device>(),
diff --git a/tensorflow/python/kernel_tests/random/random_ops_test.py b/tensorflow/python/kernel_tests/random/random_ops_test.py
index 0ef6a95cfc9..d199a9d9dd5 100644
--- a/tensorflow/python/kernel_tests/random/random_ops_test.py
+++ b/tensorflow/python/kernel_tests/random/random_ops_test.py
@@ -320,6 +320,15 @@ class RandomUniformTest(RandomOpTestCommon):
       error = np.abs(counts - mean)
       self.assertLess(error.max(), 5 * std)
 
+  # Check that minval = maxval is fine iff we're producing no numbers
+  def testUniformIntsDegenerate(self):
+    for dt in dtypes.int32, dtypes.int64:
+      def sample(n):
+        return self._Sampler(n, minv=0, maxv=0, dtype=dt, use_gpu=True)()
+      self.assertEqual(sample(0).shape, (10, 0))
+      with self.assertRaisesOpError('Need minval < maxval, got 0 >= 0'):
+        sample(1)
+
   # Checks that the CPU and GPU implementation returns the same results,
   # given the same random seed
   def testCPUGPUMatch(self):