def test_relu_node(self):
node_def = helper.make_node(
"Relu", ["X"], ["Y"])
X = np.random.randn(3, 2).astype(np.float32)
# Testing with a list
output = c2.run_node(
node_def, [X])
Y_ref = np.clip(X, 0, np.inf)
np.testing.assert_almost_equal(output["Y"], Y_ref)
# Testing with a dictionary
output = c2.run_node(
node_def, {"X": X})
Y_ref = np.clip(X, 0, np.inf)
np.testing.assert_almost_equal(output["Y"], Y_ref)
def test_gemm(self):
# simple
A = np.random.randn(3, 2).astype(np.float32)
B = np.random.randn(2, 4).astype(np.float32)
C = np.random.randn(3, 4).astype(np.float32)
node_def = make_node('Gemm', ['A', 'B', 'C'], ["Y"])
output = c2.run_node(node_def, [A, B, C])
np.testing.assert_almost_equal(output["Y"], np.dot(A, B) + C)
# transA
A = np.transpose(A)
node_def = make_node('Gemm', ['A', 'B', 'C'], ["Y"], transA=True)
output = c2.run_node(node_def, [A, B, C])
np.testing.assert_almost_equal(output["Y"],
np.dot(np.transpose(A), B) + C)
# revert A
A = np.transpose(A)
# transB
B = np.transpose(B)
node_def = make_node('Gemm', ['A', 'B', 'C'], ["Y"], transB=True)
output = c2.run_node(node_def, [A, B, C])
np.testing.assert_almost_equal(output["Y"],
np.dot(A, np.transpose(B)) + C)
# revert A
B = np.transpose(B)
# scale
alpha = np.random.random()
beta = np.random.random()
node_def = make_node('Gemm', ['A', 'B', 'C'], ["Y"],
alpha=alpha,
beta=beta)
output = c2.run_node(node_def, [A, B, C])
np.testing.assert_almost_equal(output["Y"],
alpha * np.dot(A, B) + beta * C)
# broadcast
C = np.random.randn(4).astype(np.float32)
node_def = make_node('Gemm', ['A', 'B', 'C'], ["Y"],
alpha=alpha,
beta=beta,
broadcast=1)
output = c2.run_node(node_def, [A, B, C])
np.testing.assert_almost_equal(output["Y"],
alpha * np.dot(A, B) + beta * C)
def test_relu_graph(self):
X = np.random.randn(3, 2).astype(np.float32)
Y_ref = np.clip(X, 0, np.inf)
node_def = make_node(
"Relu", ["X"], ["Y"])
output = c2.run_node(
node_def, {"X": X})
np.testing.assert_almost_equal(output.Y, Y_ref)
graph_def = make_graph(
[node_def],
name="test",
inputs=[make_tensor_value_info("X", onnx.TensorProto.FLOAT, [3, 2])],
outputs=[make_tensor_value_info("Y", onnx.TensorProto.FLOAT, [3, 2])])
c2_rep = c2.prepare(make_model(graph_def))
output = c2_rep.run(X)
np.testing.assert_almost_equal(output.Y, Y_ref)
def test_relu_node_inplace(self):
node_def = helper.make_node(
"Relu", ["X"], ["Y"], consumed_inputs=[1])
X = np.random.randn(3, 2).astype(np.float32)
output = c2.run_node(
node_def, {"X": X})
graph_def = helper.make_graph(
[node_def],
name="test",
inputs=["X"],
outputs=["X", "Y"])
Y_ref = np.clip(X, 0, np.inf)
c2_rep = c2.prepare(graph_def)
output = c2_rep.run({"X": X})
# With the inplace change from Zach, there shouldn't be Y
# np.testing.assert_almost_equal(output["Y"], Y_ref)
# ensure we wrote over X
np.testing.assert_almost_equal(output["X"], Y_ref)
