import sys import migraphx try: import numpy as np except: sys.exit() def test_conv_relu(): p = migraphx.parse_onnx("conv_relu_maxpool_test.onnx") print(p) print("Compiling ...") p.compile(migraphx.get_target("gpu")) print(p) params = {} for key, value in p.get_parameter_shapes().items(): print("Parameter {} -> {}".format(key, value)) params[key] = migraphx.generate_argument(value) r = p.run(params) print(r) def test_sub_uint64(): p = migraphx.parse_onnx("implicit_sub_bcast_test.onnx") print(p) print("Compiling ...") p.compile(migraphx.get_target("gpu")) print(p) params = {} shapes = p.get_parameter_shapes() params["0"] = np.arange(120).reshape(shapes["0"].lens()).astype(np.uint64) params["1"] = np.arange(20).reshape(shapes["1"].lens()).astype(np.uint64) r = p.run(params) print(r) def test_neg_int64(): p = migraphx.parse_onnx("neg_test.onnx") print(p) print("Compiling ...") p.compile(migraphx.get_target("gpu")) print(p) params = {} shapes = p.get_parameter_shapes() params["0"] = np.arange(6).reshape(shapes["0"].lens()).astype(np.int64) r = p.run(params) print(r) def test_nonzero(): p = migraphx.parse_onnx("nonzero_dynamic_test.onnx") print(p) print("Compiling ...") p.compile(migraphx.get_target("gpu")) print(p) params = {} shapes = p.get_parameter_shapes() params["data"] = np.array([1, 1, 0, 1]).reshape( shapes["data"].lens()).astype(np.bool) r = p.run(params) print(r) def test_fp16_imagescaler(): p = migraphx.parse_onnx("imagescaler_half_test.onnx") print(p) s1 = p.get_output_shapes()[-1] print("Compiling ...") p.compile(migraphx.get_target("gpu")) print(p) s2 = p.get_output_shapes()[-1] assert s1 == s2 params = {} shapes = p.get_parameter_shapes() params["0"] = np.random.randn(768).reshape(shapes["0"].lens()).astype( np.float16) r = p.run(params)[-1] print(r) def test_if_pl(): p = migraphx.parse_onnx("if_pl_test.onnx") print(p) s1 = p.get_output_shapes()[-1] print("Compiling ...") p.compile(migraphx.get_target("gpu")) print(p) s2 = p.get_output_shapes()[-1] assert s1 == s2 params = {} shapes = p.get_parameter_shapes() params["x"] = np.ones(6).reshape(shapes["x"].lens()).astype(np.float32) params["y"] = np.array([2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ]).reshape(shapes["y"].lens()).astype(np.float32) params["cond"] = np.array([1]).reshape(()).astype(np.bool) r = p.run(params)[-1] print(r) test_conv_relu() test_sub_uint64() test_neg_int64() test_fp16_imagescaler() test_if_pl() test_nonzero()