ashutosh-arm commented on code in PR #12353: URL: https://github.com/apache/tvm/pull/12353#discussion_r951508497
########## tests/python/contrib/test_cmsisnn/test_fuse_pads.py: ########## @@ -0,0 +1,340 @@ +# 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. + +"""CMSIS-NN integration tests: fuse_pads pass""" +import numpy as np +import pytest +import tvm +import tvm.testing +from tvm import relay +from .utils import CheckForPadsWithinCompositeFunc + +tvm._ffi._init_api("relay.ext.cmsisnn.transform", __name__) + + +def set_external_func_attr(func, compiler, ext_symbol): + func = func.with_attr("Primitive", tvm.tir.IntImm("int32", 1)) + func = func.with_attr("Compiler", compiler) + func = func.with_attr("global_symbol", ext_symbol) + return func + + +def set_composite_func_attr(func, name): + func = func.with_attr("Composite", name) + return func + + [email protected]( + "ifm_shape, pad_width, conv2d_padding, ofm_shape", + [ + [(1, 25, 25, 12), ((0, 0), (0, 2), (1, 2), (0, 0)), (1, 1, 1, 1), (1, 26, 28, 2)], + [(1, 64, 100, 4), ((0, 0), (1, 3), (1, 1), (0, 0)), (0, 0, 0, 0), (1, 64, 100, 2)], + [(1, 55, 55, 3), ((0, 0), (2, 1), (3, 5), (0, 0)), (0, 0, 1, 1), (1, 57, 59, 2)], + ], +) +def test_invalid_padding_for_fusion(ifm_shape, pad_width, conv2d_padding, ofm_shape): + """Negative tests for pads preceding Conv2D that cannot be fused.""" + dtype = "int8" + kernel_size = (3, 3) + ofm_channels = 2 + local_input = relay.var("local_input", shape=ifm_shape, dtype=dtype) + pad = relay.nn.pad( + local_input, + pad_width=pad_width, # ((), (top, bottom), (left, right), ()) + pad_value=10, + pad_mode="constant", + ) + rng = np.random.default_rng(12321) + local_weight = tvm.nd.array( + rng.integers( + np.iinfo(dtype).min, + high=np.iinfo(dtype).max, + size=(ofm_channels, kernel_size[0], kernel_size[1], ifm_shape[3]), + dtype=dtype, + ) + ) + local_weight = relay.const(local_weight, dtype) + conv2d = relay.qnn.op.conv2d( + pad, + local_weight, + relay.const(1, "int32"), + relay.const(1, "int32"), + relay.const(1, "float32"), + relay.const(1, "float32"), + data_layout="NHWC", + kernel_layout="OHWI", + channels=ofm_channels, + kernel_size=(3, 3), + padding=conv2d_padding, + out_dtype="int32", + ) + requantize = relay.qnn.op.requantize( + conv2d, + relay.const(1, "float32"), + relay.const(1, "int32"), + relay.const(1, "float32"), + relay.const(1, "int32"), + axis=0, + out_dtype=dtype, + ) + local_func = relay.Function(relay.analysis.free_vars(requantize), requantize) + local_func = set_composite_func_attr(local_func, "cmsis-nn.qnn_conv2d") + + mod = tvm.IRModule() + ext_input = relay.var("ext_input", shape=ifm_shape, dtype=dtype) + call_local_func = relay.Call(local_func, [ext_input]) + extern_func = relay.Function(relay.analysis.free_vars(call_local_func), call_local_func) + extern_var = relay.GlobalVar("external_function") + extern_func = set_external_func_attr(extern_func, "cmsis-nn", extern_var.name_hint) + mod[extern_var] = extern_func + + main_input = relay.var("main_input", shape=ifm_shape, dtype=dtype) + call_extern_func = relay.Call(extern_var, [main_input]) + main_func = relay.Function([main_input], call_extern_func, relay.TensorType(ofm_shape, dtype)) + main_var = relay.GlobalVar("main") + mod[main_var] = main_func + + mod = relay.transform.InferType()(mod) + + error_regex = r"Difference on each side of a dimension should be either 0 or 1" Review Comment: I intentionally ignored that bit as it requires re-derivation of combined padding in the test. In case we make the combined padding golden (make the absolute values as test params), we could extend the error message. A part of it is being done through `InferType()` just before it as `ofm_shape` was added as a golden value to the test. Another reason for not extending it was that the message specifically originates from the `CMSISNNFusePads()`. Plus this is the only pass that is being invoked. wdyt? -- 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]
