def verify_reverse(dshape, axis):
x = relay.var('x', relay.TensorType(dshape, 'float32'))
z = relay.reverse(x, axis=axis)
zz = run_infer_type(z)
func = relay.Function([x], z)
x_data = np.random.uniform(low=(- 1), high=1, size=dshape).astype('float32')
ref_res = np.flip(x_data, axis)
for (target, ctx) in tvm.testing.enabled_targets():
for kind in ['graph', 'debug']:
intrp = relay.create_executor(kind, ctx=ctx, target=target)
op_res = intrp.evaluate(func)(x_data)
tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-05)
def verify_reverse(dshape, axis):
x = relay.var("x", relay.TensorType(dshape, "float32"))
z = relay.reverse(x, axis=axis)
zz = relay.ir_pass.infer_type(z)
func = relay.Function([x], z)
x_data = np.random.uniform(low=-1, high=1, size=dshape).astype("float32")
ref_res = np.flip(x_data, axis)
for target, ctx in ctx_list():
for kind in ["graph", "debug"]:
intrp = relay.create_executor(kind, ctx=ctx, target=target)
op_res = intrp.evaluate(func)(x_data)
tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-5)
def verify_reverse(dshape, axis):
x = relay.var("x", relay.TensorType(dshape, "float32"))
z = relay.reverse(x, axis=axis)
zz = relay.ir_pass.infer_type(z)
func = relay.Function([x], z)
x_data = np.random.uniform(low=-1, high=1, size=dshape).astype("float32")
ref_res = np.flip(x_data, axis)
for target, ctx in ctx_list():
for kind in ["graph", "debug"]:
intrp = relay.create_executor(kind, ctx=ctx, target=target)
op_res = intrp.evaluate(func)(x_data)
tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-5)
