Mousius commented on code in PR #13522: URL: https://github.com/apache/tvm/pull/13522#discussion_r1040155081
########## tests/python/relay/aot/test_crt_forward_declarations.py: ########## @@ -0,0 +1,325 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +"""test forward function declarations codegen by CodegenCHost.""" + +from collections import OrderedDict +import pytest +import numpy as np + +import tvm.testing +from tvm import relay +from tvm.contrib.download import download_testdata +from tvm.relay.op.contrib import cmsisnn +from tvm.testing.aot import AOTTestModel, compile_models, generate_ref_data +from tvm.micro.testing.aot_test_utils import ( + AOT_CORSTONE300_RUNNER, + AOT_USMP_CORSTONE300_RUNNER, + parametrize_aot_options, + AOTTestRunner, +) + + +def skip_if_no_reference_system(func): + return tvm.testing.skip_if_32bit(reason="Reference system unavailable in i386 container")(func) Review Comment: Can we use `@tvm.testing.requires_corstone300` instead? ########## tests/python/relay/aot/test_crt_forward_declarations.py: ########## @@ -0,0 +1,325 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +"""test forward function declarations codegen by CodegenCHost.""" + +from collections import OrderedDict +import pytest +import numpy as np + +import tvm.testing +from tvm import relay +from tvm.contrib.download import download_testdata +from tvm.relay.op.contrib import cmsisnn +from tvm.testing.aot import AOTTestModel, compile_models, generate_ref_data +from tvm.micro.testing.aot_test_utils import ( + AOT_CORSTONE300_RUNNER, + AOT_USMP_CORSTONE300_RUNNER, + parametrize_aot_options, + AOTTestRunner, +) + + +def skip_if_no_reference_system(func): + return tvm.testing.skip_if_32bit(reason="Reference system unavailable in i386 container")(func) + + +def get_range_for_dtype_str(dtype): Review Comment: This function is only used once and with a fixed dtype so it doesn't feel necessary to include it just for that, could we either move it to a testing util or just hardcode the range? ########## tests/python/relay/aot/test_crt_forward_declarations.py: ########## @@ -0,0 +1,325 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +"""test forward function declarations codegen by CodegenCHost.""" + +from collections import OrderedDict +import pytest +import numpy as np + +import tvm.testing +from tvm import relay +from tvm.contrib.download import download_testdata +from tvm.relay.op.contrib import cmsisnn +from tvm.testing.aot import AOTTestModel, compile_models, generate_ref_data +from tvm.micro.testing.aot_test_utils import ( + AOT_CORSTONE300_RUNNER, + AOT_USMP_CORSTONE300_RUNNER, + parametrize_aot_options, + AOTTestRunner, +) + + +def skip_if_no_reference_system(func): + return tvm.testing.skip_if_32bit(reason="Reference system unavailable in i386 container")(func) + + +def get_range_for_dtype_str(dtype): + """ + Produces the min,max for a give data type. + + Parameters + ---------- + dtype : str + a type string (e.g., int8) + + Returns + ------- + type_info.min : int + the minimum of the range + type_info.max : int + the maximum of the range + """ + + try: + type_info = np.iinfo(dtype) + except ValueError: + type_info = np.finfo(dtype) + return type_info.min, type_info.max + + +# pylint: disable=import-outside-toplevel +def _convert_to_relay( Review Comment: Can we add a `load_from_file` to here: https://github.com/apache/tvm/blob/72e11baabb0e3a7e311c4b3490b729641c489555/python/tvm/relay/testing/tflite.py#L29 So it's just: ``` TFLiteModel.from_buffer(buf).convert_to_relay() ``` rather than recreating parts of that class here? ########## tests/python/relay/aot/test_crt_forward_declarations.py: ########## @@ -0,0 +1,325 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +"""test forward function declarations codegen by CodegenCHost.""" + +from collections import OrderedDict +import pytest +import numpy as np + +import tvm.testing +from tvm import relay +from tvm.contrib.download import download_testdata +from tvm.relay.op.contrib import cmsisnn +from tvm.testing.aot import AOTTestModel, compile_models, generate_ref_data +from tvm.micro.testing.aot_test_utils import ( + AOT_CORSTONE300_RUNNER, + AOT_USMP_CORSTONE300_RUNNER, + parametrize_aot_options, + AOTTestRunner, +) + + +def skip_if_no_reference_system(func): + return tvm.testing.skip_if_32bit(reason="Reference system unavailable in i386 container")(func) + + +def get_range_for_dtype_str(dtype): + """ + Produces the min,max for a give data type. + + Parameters + ---------- + dtype : str + a type string (e.g., int8) + + Returns + ------- + type_info.min : int + the minimum of the range + type_info.max : int + the maximum of the range + """ + + try: + type_info = np.iinfo(dtype) + except ValueError: + type_info = np.finfo(dtype) + return type_info.min, type_info.max + + +# pylint: disable=import-outside-toplevel +def _convert_to_relay( + tflite_model_buf, + input_data, + input_node, +): + """Converts TFLite model to Relay module and params""" + + def convert_to_list(x): + if not isinstance(x, list): + x = [x] + return x + + # TFLite.Model.Model has changed to TFLite.Model from 1.14 to 2.1 + try: + import tflite.Model + + tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0) + except AttributeError: + import tflite + + tflite_model = tflite.Model.GetRootAsModel(tflite_model_buf, 0) + except ImportError: + raise ImportError("The tflite package must be installed") + + input_data = convert_to_list(input_data) + input_node = convert_to_list(input_node) + + shape_dict = {} + dtype_dict = {} + for i, name in enumerate(input_node): + shape_dict[name] = input_data[i].shape + dtype_dict[name] = input_data[i].dtype.name + + mod, params = relay.frontend.from_tflite( + tflite_model, shape_dict=shape_dict, dtype_dict=dtype_dict + ) + + return mod, params + + +def _change_ndarray_layout(arr, src_layout, dst_layout): + """Makes a copy of an ndarray, reshaping it to a new data layout. + + Parameter + --------- + arr : numpy.ndarray + The ndarray to be reformatted. + + src_layout : str + The current layout of the Relay constant. Must be alphabetic (e.g. NHWC + or OIHW, but not NCHW2c). + + dst_layout : str + The desired layout of new the Relay constant. Must be alphabetic (e.g. NHWC + or OIHW, but not NCHW2c). + + Returns + ------- + dst_shape : numpy.ndarray + A copy of the ndarray with the new layout. + """ + assert src_layout.isalpha() and dst_layout.isalpha() + axis_order = [src_layout.index(c) for c in dst_layout] + return np.transpose(arr, axis_order) + + [email protected]_package("tflite") [email protected]_cmsisnn [email protected]("test_runner", [AOT_CORSTONE300_RUNNER, AOT_USMP_CORSTONE300_RUNNER]) +def test_external_calls(test_runner): + """Download a small network and partition for CMSIS-NN to test forward declarations for external + calls outside of __tvm_main__.""" + # download the model + base_url = ( + "https://github.com/ARM-software/ML-zoo/raw/"; + "48a22ee22325d15d2371a6df24eb7d67e21dcc97" + "/models/keyword_spotting/cnn_small/tflite_int8" + ) + file_to_download = "cnn_s_quantized.tflite" + file_saved = "cnn_s_quantized_15Dec2021.tflite" + model_file = download_testdata("{}/{}".format(base_url, file_to_download), file_saved) + + with open(model_file, "rb") as f: + tflite_model_buf = f.read() + + input_shape = (1, 490) + dtype = "int8" + in_min, in_max = get_range_for_dtype_str(dtype) + rng = np.random.default_rng(12345) + input_data = rng.integers(in_min, high=in_max, size=input_shape, dtype=dtype) + + orig_mod, params = _convert_to_relay(tflite_model_buf, input_data, "input") + cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod, params) + + # validate CMSIS-NN output against CPU output + interface_api = "c" + use_unpacked_api = True + inputs = {"input": input_data} + params = {} + output_list = generate_ref_data(orig_mod["main"], inputs, params) + compiled_models = compile_models( + AOTTestModel( + module=cmsisnn_mod, + inputs=inputs, + outputs=output_list, + params=None, + output_tolerance=1, + ), + interface_api, + use_unpacked_api, + pass_config=test_runner.pass_config, + ) + + # Forward function declaration increases the number of times a function name appears under + # __tvm__main. Validate this frequency for native, offloaded and allocation functions. + lib_mod = compiled_models[0].executor_factory.lib.imported_modules[0] + main_source = lib_mod.get_source() + assert ( + main_source.count("TVMBackendAllocWorkspace") == 3 + or main_source.count("TVMBackendAllocWorkspace") == 0 + ) + assert main_source.count("tvmgen_default_fused_reshape") == 2 + assert main_source.count("tvmgen_default_cmsis_nn_main") == 12 + cmsisnn_source = lib_mod.imported_modules[0].get_source() + assert cmsisnn_source.count("arm_convolve_wrapper") == 1 + assert cmsisnn_source.count("arm_fully_connected") == 3 + assert cmsisnn_source.count("arm_softmax") == 1 + + +@parametrize_aot_options +def test_internal_calls(interface_api, use_unpacked_api, test_runner): + """Test for all internal function calls. No forward declarations are expected here.""" + dtype = "float32" + groups = 32 + weight_shape = 1 + ishape = (1, 32, 14, 14) + wshape = (32, weight_shape, 3, 3) + pass_config = {"tir.usmp.enable": True} + test_runner = AOTTestRunner( + makefile=test_runner.makefile, + prologue=test_runner.prologue, + epilogue=test_runner.epilogue, + includes=test_runner.includes, + parameters=test_runner.parameters, + pass_config=pass_config, + ) + + data0 = relay.var("data", shape=ishape, dtype=dtype) + weight0 = relay.var("weight", shape=wshape, dtype=dtype) + out = relay.nn.conv2d(data0, weight0, kernel_size=(3, 3), padding=(1, 1), groups=groups) + main_f = relay.Function([data0, weight0], out) + mod = tvm.IRModule() + mod["main"] = main_f + mod = tvm.relay.transform.InferType()(mod) + + i_data = np.random.uniform(0, 1, ishape).astype(dtype) + w1_data = np.random.uniform(0, 1, wshape).astype(dtype) + + inputs = OrderedDict([("data", i_data), ("weight", w1_data)]) + + output_list = generate_ref_data(mod, inputs) + compiled_models = compile_models( + models=AOTTestModel(module=mod, inputs=inputs, outputs=output_list), + interface_api=interface_api, + use_unpacked_api=use_unpacked_api, + pass_config=test_runner.pass_config, + ) + + lib_mod = compiled_models[0].executor_factory.lib.imported_modules[0] + main_source = lib_mod.get_source() + assert main_source.count("tvmgen_default_fused_nn_contrib_depthwise_conv2d_NCHWc") == 2 + assert main_source.count("tvmgen_default_fused_layout_transform") == 6 + + +@skip_if_no_reference_system [email protected]_cmsisnn +def test_tensorized_calls(): + """Test a subgraph with a mix of internal and tensorized calls.""" + data_shape, kernel_size, num_filter, groups, strides, padding, dilation = ( + (1, 32, 32, 16), + (3, 3), + 16, + 1, + 1, + (0, 2, 2, 0), + 1, + ) + in_dtype = "int8" + data_layout = "NHWC" + kernel_layout = "HWOI" + ref_kernel_layout = "HWIO" + out_layout = "NHWC" + schedule_name = "conv2d_nhwc_dsp.arm_cpu" + + ref_input_data = np.random.randint(low=-128, high=127, size=data_shape, dtype=in_dtype) + ref_input_var = relay.var("input", relay.TensorType(data_shape, in_dtype)) # NHWC layout + kernel_shape = (*kernel_size, data_shape[-1] // groups, num_filter) # HWIO layout + ref_kernel_data = np.random.randint(low=-10, high=10, size=kernel_shape, dtype=in_dtype) + + ref_relay_op = relay.op.nn.conv2d( + ref_input_var, + relay.const(_change_ndarray_layout(ref_kernel_data, "HWIO", ref_kernel_layout)), + kernel_size=kernel_size, + strides=strides, + padding=padding, + groups=groups, + dilation=(dilation, dilation), + data_layout="NHWC", + kernel_layout=ref_kernel_layout, + out_dtype="int32", + out_layout="NHWC", + ) + ref_module = tvm.IRModule.from_expr(relay.Function([ref_input_var], ref_relay_op)) + ref_outputs = generate_ref_data(ref_module, {"input": ref_input_data}) + + # Reshape output dictionary to match out_layout + assert len(ref_outputs) == 1 + output_tensor_name, output_tensor = next(iter(ref_outputs.items())) + ref_outputs[output_tensor_name] = _change_ndarray_layout(output_tensor, "NHWC", out_layout) + + test_input_data = _change_ndarray_layout(ref_input_data, "NHWC", data_layout) + test_input_var = relay.var("input", relay.TensorType(test_input_data.shape, in_dtype)) + test_kernel_data = _change_ndarray_layout(ref_kernel_data, "HWIO", kernel_layout) + + test_relay_op = relay.op.nn.conv2d( + test_input_var, + relay.const(test_kernel_data), + kernel_size=kernel_size, + strides=strides, + padding=padding, + groups=groups, + dilation=(dilation, dilation), + data_layout=data_layout, + kernel_layout=kernel_layout, + out_dtype="int32", + out_layout=out_layout, + ) + test_function = relay.Function([test_input_var], test_relay_op) + test_model = AOTTestModel( + module=tvm.IRModule.from_expr(test_function), + inputs={"input": test_input_data}, + outputs=ref_outputs, + ) + compiled_models = compile_models( + test_model, + interface_api="c", + use_unpacked_api=True, + pass_config=AOT_CORSTONE300_RUNNER.pass_config, + target=f"c -keys=arm_cpu -mcpu=cortex-m7", + schedule_name=schedule_name, + ) + + lib_mod = compiled_models[0].executor_factory.lib.imported_modules[0] + main_source = lib_mod.get_source() + assert main_source.count("tvmgen_default_fused_nn_conv2d") == 2 + assert main_source.count("gemm_") == 13 Review Comment: We should consider using a test-oriented schedules/BYOC here rather than these tests being dependent on a specific implementation elsewhere in the codebase - this is fine for now though. ########## tests/python/relay/aot/test_crt_forward_declarations.py: ########## @@ -0,0 +1,325 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +"""test forward function declarations codegen by CodegenCHost.""" + +from collections import OrderedDict +import pytest +import numpy as np + +import tvm.testing +from tvm import relay +from tvm.contrib.download import download_testdata +from tvm.relay.op.contrib import cmsisnn +from tvm.testing.aot import AOTTestModel, compile_models, generate_ref_data +from tvm.micro.testing.aot_test_utils import ( + AOT_CORSTONE300_RUNNER, + AOT_USMP_CORSTONE300_RUNNER, + parametrize_aot_options, + AOTTestRunner, +) + + +def skip_if_no_reference_system(func): + return tvm.testing.skip_if_32bit(reason="Reference system unavailable in i386 container")(func) + + +def get_range_for_dtype_str(dtype): + """ + Produces the min,max for a give data type. + + Parameters + ---------- + dtype : str + a type string (e.g., int8) + + Returns + ------- + type_info.min : int + the minimum of the range + type_info.max : int + the maximum of the range + """ + + try: + type_info = np.iinfo(dtype) + except ValueError: + type_info = np.finfo(dtype) + return type_info.min, type_info.max + + +# pylint: disable=import-outside-toplevel +def _convert_to_relay( + tflite_model_buf, + input_data, + input_node, +): + """Converts TFLite model to Relay module and params""" + + def convert_to_list(x): + if not isinstance(x, list): + x = [x] + return x + + # TFLite.Model.Model has changed to TFLite.Model from 1.14 to 2.1 + try: + import tflite.Model + + tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0) + except AttributeError: + import tflite + + tflite_model = tflite.Model.GetRootAsModel(tflite_model_buf, 0) + except ImportError: + raise ImportError("The tflite package must be installed") + + input_data = convert_to_list(input_data) + input_node = convert_to_list(input_node) + + shape_dict = {} + dtype_dict = {} + for i, name in enumerate(input_node): + shape_dict[name] = input_data[i].shape + dtype_dict[name] = input_data[i].dtype.name + + mod, params = relay.frontend.from_tflite( + tflite_model, shape_dict=shape_dict, dtype_dict=dtype_dict + ) + + return mod, params + + +def _change_ndarray_layout(arr, src_layout, dst_layout): + """Makes a copy of an ndarray, reshaping it to a new data layout. + + Parameter + --------- + arr : numpy.ndarray + The ndarray to be reformatted. + + src_layout : str + The current layout of the Relay constant. Must be alphabetic (e.g. NHWC + or OIHW, but not NCHW2c). + + dst_layout : str + The desired layout of new the Relay constant. Must be alphabetic (e.g. NHWC + or OIHW, but not NCHW2c). + + Returns + ------- + dst_shape : numpy.ndarray + A copy of the ndarray with the new layout. + """ + assert src_layout.isalpha() and dst_layout.isalpha() + axis_order = [src_layout.index(c) for c in dst_layout] + return np.transpose(arr, axis_order) + + [email protected]_package("tflite") [email protected]_cmsisnn [email protected]("test_runner", [AOT_CORSTONE300_RUNNER, AOT_USMP_CORSTONE300_RUNNER]) +def test_external_calls(test_runner): + """Download a small network and partition for CMSIS-NN to test forward declarations for external + calls outside of __tvm_main__.""" + # download the model + base_url = ( + "https://github.com/ARM-software/ML-zoo/raw/"; + "48a22ee22325d15d2371a6df24eb7d67e21dcc97" + "/models/keyword_spotting/cnn_small/tflite_int8" + ) + file_to_download = "cnn_s_quantized.tflite" + file_saved = "cnn_s_quantized_15Dec2021.tflite" + model_file = download_testdata("{}/{}".format(base_url, file_to_download), file_saved) + + with open(model_file, "rb") as f: + tflite_model_buf = f.read() + + input_shape = (1, 490) + dtype = "int8" + in_min, in_max = get_range_for_dtype_str(dtype) + rng = np.random.default_rng(12345) + input_data = rng.integers(in_min, high=in_max, size=input_shape, dtype=dtype) + + orig_mod, params = _convert_to_relay(tflite_model_buf, input_data, "input") + cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod, params) + + # validate CMSIS-NN output against CPU output + interface_api = "c" + use_unpacked_api = True + inputs = {"input": input_data} + params = {} + output_list = generate_ref_data(orig_mod["main"], inputs, params) + compiled_models = compile_models( + AOTTestModel( + module=cmsisnn_mod, + inputs=inputs, + outputs=output_list, + params=None, + output_tolerance=1, + ), + interface_api, + use_unpacked_api, + pass_config=test_runner.pass_config, + ) + + # Forward function declaration increases the number of times a function name appears under + # __tvm__main. Validate this frequency for native, offloaded and allocation functions. Review Comment: This doesn't produce forward declarations inside `__tvm_main__`, it produces them inside the host code generation for functions that are called within `__tvm_main__`? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
