cailun01 commented on a change in pull request #8277:
URL: https://github.com/apache/tvm/pull/8277#discussion_r654288257
##########
File path: tests/python/frontend/tensorflow/test_forward.py
##########
@@ -1717,58 +1717,58 @@ def test_forward_variable():
_test_variable(np.random.uniform(size=(32, 100)).astype("float32"))
[email protected]_targets("llvm", "cuda")
-def test_read_variable_op(target, dev):
- """Read Variable op test"""
-
- tf.reset_default_graph()
- data = np.random.uniform(size=(32, 100)).astype("float32")
- input_tensor = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
-
- size = input_tensor.shape.dims[1]
- var_data = np.random.uniform(-5, 5, size=[size, size]).astype(np.float32)
- input_var = tf.Variable(var_data, name="var1", use_resource=True)
- math_ops.matmul(input_tensor, input_var)
-
- out_name = ["MatMul:0"]
- out_node = ["MatMul"]
- in_name = ["Placeholder:0"]
- in_node = ["Placeholder"]
- in_data = [data]
-
- with tf.Session() as sess:
- sess.run(variables.global_variables_initializer())
-
- final_graph_def = sess.graph.as_graph_def(add_shapes=True)
- tf_output = run_tf_graph(sess, in_data, in_name, out_name)
-
- shape_dict = {e: i.shape for e, i in zip(in_name, in_data)}
- with pytest.raises(Exception) as execinfo:
- mod, params = relay.frontend.from_tensorflow(
- final_graph_def, layout=None, shape=shape_dict, outputs=None
- )
-
- assert execinfo.value.args[0].startswith("Graph is not frozen. Provide
a frozen graph")
-
- # Now convert the variables to constant and run inference on the
converted graph
- final_graph_def = tf.graph_util.convert_variables_to_constants(
- sess,
- sess.graph.as_graph_def(add_shapes=True),
- out_node,
- )
-
- tvm_output = run_tvm_graph(
- final_graph_def,
- in_data,
- in_node,
- target=target,
- out_names=out_name,
- num_output=len(out_name),
- )
- for i in range(len(tf_output)):
- tvm.testing.assert_allclose(tf_output[i], tvm_output[i],
atol=1e-4, rtol=1e-5)
-
- sess.close()
+# @tvm.testing.parametrize_targets("llvm", "cuda")
Review comment:
Sorry, I forgot to uncomment that line.
##########
File path: tests/python/frontend/tensorflow/test_forward.py
##########
@@ -1717,58 +1717,58 @@ def test_forward_variable():
_test_variable(np.random.uniform(size=(32, 100)).astype("float32"))
[email protected]_targets("llvm", "cuda")
-def test_read_variable_op(target, dev):
- """Read Variable op test"""
-
- tf.reset_default_graph()
- data = np.random.uniform(size=(32, 100)).astype("float32")
- input_tensor = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
-
- size = input_tensor.shape.dims[1]
- var_data = np.random.uniform(-5, 5, size=[size, size]).astype(np.float32)
- input_var = tf.Variable(var_data, name="var1", use_resource=True)
- math_ops.matmul(input_tensor, input_var)
-
- out_name = ["MatMul:0"]
- out_node = ["MatMul"]
- in_name = ["Placeholder:0"]
- in_node = ["Placeholder"]
- in_data = [data]
-
- with tf.Session() as sess:
- sess.run(variables.global_variables_initializer())
-
- final_graph_def = sess.graph.as_graph_def(add_shapes=True)
- tf_output = run_tf_graph(sess, in_data, in_name, out_name)
-
- shape_dict = {e: i.shape for e, i in zip(in_name, in_data)}
- with pytest.raises(Exception) as execinfo:
- mod, params = relay.frontend.from_tensorflow(
- final_graph_def, layout=None, shape=shape_dict, outputs=None
- )
-
- assert execinfo.value.args[0].startswith("Graph is not frozen. Provide
a frozen graph")
-
- # Now convert the variables to constant and run inference on the
converted graph
- final_graph_def = tf.graph_util.convert_variables_to_constants(
- sess,
- sess.graph.as_graph_def(add_shapes=True),
- out_node,
- )
-
- tvm_output = run_tvm_graph(
- final_graph_def,
- in_data,
- in_node,
- target=target,
- out_names=out_name,
- num_output=len(out_name),
- )
- for i in range(len(tf_output)):
- tvm.testing.assert_allclose(tf_output[i], tvm_output[i],
atol=1e-4, rtol=1e-5)
-
- sess.close()
+# @tvm.testing.parametrize_targets("llvm", "cuda")
Review comment:
Sorry, I've just noticed that I forgot to uncomment the whole
`test_read_variable_op`.
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