def check_static_result_4(self, place): paddle.enable_static() with program_guard(Program(), Program()): input_shape = (2, 3, 4, 5, 6) pad = [1, 2, 1, 1, 3, 4] mode = "circular" input_data = np.random.rand(*input_shape).astype(np.float32) x = paddle.fluid.data(name="x", shape=input_shape) result1 = F.pad(x=x, pad=pad, mode=mode, data_format="NCDHW") result2 = F.pad(x=x, pad=pad, mode=mode, data_format="NDHWC") exe = Executor(place) fetches = exe.run(default_main_program(), feed={"x": input_data}, fetch_list=[result1, result2]) np_out1 = self._get_numpy_out(input_data, pad, mode, data_format="NCDHW") np_out2 = self._get_numpy_out(input_data, pad, mode, data_format="NDHWC") self.assertTrue(np.allclose(fetches[0], np_out1)) self.assertTrue(np.allclose(fetches[1], np_out2))
def test_reflect_3(): input_shape = (1, 2, 3, 4, 5) data = np.random.rand(*input_shape).astype(np.float32) x = paddle.fluid.data(name="x", shape=input_shape) y = F.pad(x, pad=[1, 1, 1, 1, 2, 3], value=1, mode='reflect') place = paddle.CPUPlace() exe = Executor(place) outputs = exe.run(feed={'x': data}, fetch_list=[y.name])
def check_static_result_1(self, place): paddle.enable_static() with program_guard(Program(), Program()): input_shape = (1, 2, 3, 4, 5) pad = [1, 2, 1, 1, 3, 4] mode = "constant" value = 100 input_data = np.random.rand(*input_shape).astype(np.float32) x = paddle.fluid.data(name="x", shape=input_shape) result = F.pad(x=x, pad=pad, value=value, mode=mode, data_format="NCDHW") exe = Executor(place) fetches = exe.run(default_main_program(), feed={"x": input_data}, fetch_list=[result]) np_out = self._get_numpy_out(input_data, pad, mode, value) self.assertTrue(np.allclose(fetches[0], np_out))
def check_static_result(self, place): paddle.enable_static() with program_guard(Program(), Program()): shape = [10, 15] axis = 1 eps = 1e-8 np.random.seed(0) np_x1 = np.random.rand(*shape).astype(np.float32) np_x2 = np.random.rand(*shape).astype(np.float32) x1 = paddle.fluid.data(name="x1", shape=shape) x2 = paddle.fluid.data(name="x2", shape=shape) result = F.cosine_similarity(x1, x2, axis=axis, eps=eps) exe = Executor(place) fetches = exe.run(default_main_program(), feed={"x1": np_x1, "x2": np_x2}, fetch_list=[result]) np_out = self._get_numpy_out(np_x1, np_x2, axis=axis, eps=eps) self.assertTrue(np.allclose(fetches[0], np_out))
def test_static(self): paddle.enable_static() self.place = fluid.NPUPlace( 0) if fluid.core.is_compiled_with_npu() else fluid.CPUPlace() with program_guard(Program(), Program()): input_shape = (1, 2, 3, 4, 5) pad = [1, 2, 1, 1, 3, 4] mode = "constant" value = 0 input_data = np.random.rand(*input_shape).astype(np.float32) x = paddle.fluid.data(name="x", shape=input_shape) result1 = F.pad(x=x, pad=pad, value=value, mode=mode, data_format="NCDHW") result2 = F.pad(x=x, pad=pad, value=value, mode=mode, data_format="NDHWC") exe = Executor(self.place) fetches = exe.run(default_main_program(), feed={"x": input_data}, fetch_list=[result1, result2]) np_out1 = self._get_numpy_out(input_data, pad, mode, value, data_format="NCDHW") np_out2 = self._get_numpy_out(input_data, pad, mode, value, data_format="NDHWC") self.assertTrue(np.allclose(fetches[0], np_out1)) self.assertTrue(np.allclose(fetches[1], np_out2))