Dragan: random uniform fix (openvinotoolkit#8716)

* fix random uniform input constant layout * added test for 4D
Chararu · Nov 26, 2021 · 5b3c3bc · 5b3c3bc
1 parent 7a16de2
commit 5b3c3bc
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Showing 2 changed files with 5 additions and 1 deletion.
diff --git a/model-optimizer/extensions/ops/random_uniform.py b/model-optimizer/extensions/ops/random_uniform.py
@@ -4,6 +4,7 @@
 import numpy as np
 
 from mo.graph.graph import Graph, Node
+from mo.graph.perm_inputs import PermuteInputs
 from mo.middle.passes.convert_data_type import np_data_type_to_destination_type
 from mo.ops.op import Op
 
@@ -51,6 +52,8 @@ def infer(node: Node):
         node.in_node(1)['correct_data_type'] = True
         node.in_node(2)['correct_data_type'] = True
 
+        PermuteInputs().set_input_permutation(node.in_node(0), node, 'output:0', 'shape')
+
 
 class AttributedRandomUniform(Op):
     """ RandomUniform operation that generates a sequence of random values from uniform distribution.

diff --git a/tests/layer_tests/tensorflow_tests/test_tf_RandomUniform.py b/tests/layer_tests/tensorflow_tests/test_tf_RandomUniform.py
@@ -26,7 +26,7 @@ def create_tf_random_uniform_net(self, global_seed, op_seed, x_shape, min_val, m
             x = tf.compat.v1.placeholder(input_type, tf_x_shape, 'Input')
             if global_seed is not None:
                 tf.compat.v1.random.set_random_seed(global_seed)
-            random_uniform = tf.random.uniform(x_shape, seed=op_seed, dtype=input_type, minval=min_val,
+            random_uniform = tf.random.uniform(tf_x_shape, seed=op_seed, dtype=input_type, minval=min_val,
                                                maxval=max_val) + x
 
             tf.compat.v1.global_variables_initializer()
@@ -80,6 +80,7 @@ def create_tf_random_uniform_net(self, global_seed, op_seed, x_shape, min_val, m
         dict(global_seed=32465, op_seed=48971, min_val=0.0, max_val=1.0, x_shape=[3, 7], input_type=tf.float32),
         marks=pytest.mark.precommit),
         dict(global_seed=None, op_seed=56197, min_val=-100, max_val=100, x_shape=[6], input_type=tf.float32),
+        dict(global_seed=None, op_seed=56197, min_val=-100, max_val=100, x_shape=[1, 2, 1, 1], input_type=tf.float32),
         dict(global_seed=78132, op_seed=None, min_val=-200, max_val=-50, x_shape=[5, 8], input_type=tf.int32),
         dict(global_seed=4571, op_seed=48971, min_val=1.5, max_val=2.3, x_shape=[7], input_type=tf.float32),
         dict(global_seed=32465, op_seed=12335, min_val=-150, max_val=-100, x_shape=[18], input_type=tf.int32)]