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From GitBox <...@apache.org>
Subject [GitHub] [incubator-tvm] dhruvaray commented on a change in pull request #5329: [Frontend][TFLite] Add parser support for shape and range
Date Fri, 08 May 2020 11:02:11 GMT

dhruvaray commented on a change in pull request #5329:
URL: https://github.com/apache/incubator-tvm/pull/5329#discussion_r422081644



##########
File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -650,6 +693,82 @@ def test_all_resize():
         _test_resize(tf.image.resize_nearest_neighbor, data, align_corners=False)
 
 
+#######################################################################
+# Range
+# -----
+def _test_range(start, limit, delta):
+    # tflite 1.13 convert method does not accept empty shapes
+    if package_version.parse(tf.VERSION) >= package_version.parse('1.14.0'):
+        tf.reset_default_graph()
+        with tf.Graph().as_default():
+            start_scalar, limit_scalar, delta_scalar = \
+                tf.placeholder(dtype=start.dtype, shape=(), name="start"), \
+                tf.placeholder(dtype=limit.dtype, shape=(), name="limit"), \
+                tf.placeholder(dtype=delta.dtype, shape=(), name="delta")
+
+            out = tf.range(start_scalar, limit_scalar, delta_scalar, name="range")
+
+            compare_tflite_with_tvm(
+                [start, limit, delta],
+                ["start", "limit", "delta"],
+                [start_scalar, limit_scalar, delta_scalar],
+                [out],
+                mode="vm",
+                quantized=False
+        )
+
+def _test_range_default():
+    # tflite 1.13 convert method does not accept empty shapes
+    if package_version.parse(tf.VERSION) >= package_version.parse('1.14.0'):
+        tf.reset_default_graph()
+        with tf.Graph().as_default():
+
+            inputs = [
+                tf.placeholder(dtype=tf.int32, shape=(), name="p1"),
+                tf.placeholder(dtype=tf.int32, shape=(), name="p2")
+            ]
+            leaves = [
+                tf.range(start = inputs[0], limit = inputs[1]), #use default delta
+                tf.range(start = inputs[1]) #use start as limit with 0 as the first item
in the range
+            ]
+
+            compare_tflite_with_tvm(
+                [np.int32(1), np.int32(18)],
+                ["p1", "p2"],
+                inputs,
+                leaves,
+                mode="vm",
+                quantized=False
+        )
+
+def test_forward_range():
+   _test_range(np.int32(1), np.int32(18), np.int32(3))
+   _test_range(np.int32(1), np.int32(18), np.float32(3.1)) # increment is of type float
+   _test_range(np.float32(1.0), np.int32(18), np.int32(3.1)) # start is of type float
+   _test_range_default()
+
+#######################################################################
+# Shape
+# -----
+def test_forward_shape():
+    # tflite 1.13 convert method does not accept empty shapes
+    if package_version.parse(tf.VERSION) >= package_version.parse('1.14.0'):
+        tf.reset_default_graph()
+        with tf.Graph().as_default():
+            data = np.array([1, 18, 3], dtype=np.int32)
+            start = tf.placeholder(dtype=tf.int32, shape=[], name="start")
+            limit = tf.placeholder(dtype=tf.int32, shape=[], name="limit")
+            delta = tf.placeholder(dtype=tf.int32, shape=[], name="delta")
+            r = tf.range(start, limit, delta, tf.int32, name="range")
+            out = tf.shape(r, out_type=tf.dtypes.int32)
+            compare_tflite_with_tvm(
+                [x for x in np.nditer(data)],
+                ["start", "limit", "delta"],
+                [start, limit, delta],
+                [out],
+                mode="vm",
+                quantized=False
+            )
 #######################################################################

Review comment:
       added




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