Update framework test generator to support TF/TFL conv3d.

Add a new attribute `rank` to indicate the testing dimension range of
input tensor. Also fix a minor bug in the existing conv3d simulation.
And relax rescale operator in the reference model to support 5-D input.

Change-Id: Ib42fe513831dc83eb7f9af07e011787a6c752704
Signed-off-by: TatWai Chong <tatwai.chong@arm.com>

1 files changed, 41 insertions, 0 deletions

diff --git a/verif/frameworks/test_builder.py b/verif/frameworks/test_builder.py
index 84e4d46..0468518 100644
--- a/verif/frameworks/test_builder.py
+++ b/verif/frameworks/test_builder.py
@@ -479,6 +479,47 @@ class TBuilder:
             )
             return bias_add_op
 
+    class Conv3d:
+        def __init__(self, weight, strides, padding, dilations, name):
+            self.weight = weight
+            self.strides = strides
+            self.padding = padding
+            self.dilations = dilations
+            self.result_name = name
+
+        def eval(self, input):
+            return tf.nn.conv3d(
+                input,
+                self.weight,
+                self.strides,
+                self.padding,
+                data_format="NDHWC",
+                dilations=self.dilations,
+                name=self.result_name,
+            )
+
+    class Conv3dWithBias:
+        def __init__(self, weight, bias, strides, padding, dilations, name):
+            self.weight = weight
+            self.bias = bias
+            self.strides = strides
+            self.padding = padding
+            self.dilations = dilations
+            self.result_name = name
+
+        def eval(self, input):
+            conv3d_op = tf.nn.conv3d(
+                input,
+                self.weight,
+                self.strides,
+                self.padding,
+                data_format="NDHWC",
+                dilations=self.dilations,
+                name="conv3d",
+            )
+            bias_add_op = tf.nn.bias_add(conv3d_op, self.bias, name=self.result_name)
+            return bias_add_op
+
     class DepthwiseConv2d:
         def __init__(self, weight, strides, padding, dilations, name):
             self.weight = weight