cconvey commented on code in PR #11417: URL: https://github.com/apache/tvm/pull/11417#discussion_r882707828
########## tests/python/contrib/test_hexagon/test_avg_pool2d_slice.py: ########## @@ -0,0 +1,434 @@ +# 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. + +import pytest +import numpy as np + +np.set_printoptions(threshold=np.inf) +from tvm import te, topi +from tvm.tir.stmt_functor import post_order_visit + +import tvm.testing +from tvm.topi import testing +from tvm.contrib.hexagon.build import HexagonLauncher +import tvm.topi.hexagon.slice_ops as sl +from .infrastructure import allocate_hexagon_array, transform_numpy + + +input_layout = tvm.testing.parameter( + "nhwc-8h2w32c2w", +) + + +@tvm.testing.fixture +def input_np(input_shape, dtype): + return np.random.random(input_shape).astype(dtype) + + +@tvm.testing.fixture +def transformed_expected_output_np(expected_output_np, output_layout): + return transform_numpy(expected_output_np, output_layout) + + +@tvm.testing.fixture +def transformed_input_np_padded(input_np_padded, input_layout): + return transform_numpy(input_np_padded, input_layout) + + +class TestAvgPool2dSlice: + # NOTE: input_layout is always assumed to be "nhwc-8h2w32c2w" + ( + output_shape, + kernel, + stride, + dilation, + padding, + ceil_mode, + count_include_pad, + output_layout, + dtype, + use_te_sched, + ) = tvm.testing.parameters( + ( + [1, 8, 8, 32], + [3, 3], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 16, 16, 32], + [3, 3], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 8, 8, 32], + [8, 8], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 8, 8, 32], + [1, 1], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + # Test non-one stride and dilation + ( + [1, 8, 8, 32], + [3, 3], + [2, 3], + [1, 1], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 8, 8, 32], + [3, 3], + [2, 2], + [2, 2], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 8, 8, 32], + [3, 3], + [2, 2], + [2, 3], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + # Test non-zero padding + ( + [1, 8, 8, 32], + [3, 3], + [1, 1], + [1, 1], + [1, 1, 1, 1], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 8, 8, 32], + [3, 3], + [1, 1], + [1, 1], + [1, 2, 3, 4], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 8, 8, 32], + [3, 3], + [1, 1], + [1, 1], + [1, 2, 3, 4], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + ( + [1, 8, 8, 32], + [3, 3], + [3, 2], + [2, 3], + [1, 2, 3, 4], + False, + True, + "nhwc-8h2w32c2w", + "float16", + False, + ), + # Test n11c-1024c layout which will require input and output to have different layout + ( + [1, 1, 1, 2048], + [8, 8], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "n11c-1024c", + "float16", + False, + ), + ( + [1, 1, 1, 2048], + [6, 6], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "n11c-1024c", + "float16", + False, + ), + ( + [1, 1, 1, 2048], + [3, 3], + [2, 2], + [1, 1], + [0, 0, 0, 0], + False, + True, + "n11c-1024c", + "float16", + False, + ), + ( + [1, 1, 1, 2048], + [4, 4], + [2, 2], + [2, 3], + [0, 0, 0, 0], + False, + True, + "n11c-1024c", + "float16", + False, + ), + # Use 'te' schedule + ( + [1, 8, 8, 32], + [3, 3], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "nhwc-8h2w32c2w", + "float16", + True, + ), + ( + [1, 1, 1, 2048], + [8, 8], + [1, 1], + [1, 1], + [0, 0, 0, 0], + False, + True, + "n11c-1024c", + "float16", + True, + ), + ) + + @tvm.testing.fixture + def expected_output_np( + self, + input_np, + kernel, + stride, + dilation, + padding, + ceil_mode, + count_include_pad, + ): + pad_before = padding[:2] + pad_after = padding[2:] + ref_np = tvm.topi.testing.poolnd_python( + input_np, + kernel, + stride, + dilation, + pad_before, + pad_after, + "avg", # pool_type + count_include_pad, + False, # ceil_mode, + layout="NHWC", + ) + return ref_np + + @tvm.testing.fixture + def input_shape(self, output_shape, kernel, padding, stride, dilation, output_layout): + # Input shape without crouton padding; 'ceil' is being ignored from calculation: + o_b, o_h, o_w, o_c = output_shape + d_h, d_w = dilation + s_h, s_w = stride + k_h, k_w = kernel + pad_before_h, pad_before_w = padding[:2] + pad_after_h, pad_after_w = padding[2:] + + if output_layout == "n11c-1024c": + assert ( + pad_before_w == 0 and pad_after_w == 0 and pad_before_h == 0 and pad_after_h == 0 + ), "Padding must be zero for n11c-1024c layout!!" + assert o_h == 1 and o_w == 1, "Output height and width must be 1!" + + in_h = (o_h - 1) * s_h + d_h * (k_h - 1) + 1 - pad_before_h - pad_after_h + in_w = (o_w - 1) * s_w + d_w * (k_w - 1) + 1 - pad_before_w - pad_after_w + + return [o_b, in_h, in_w, o_c] + + @tvm.testing.fixture + def input_shape_padded(self, input_shape, padding, output_layout): + # Input shape with regular and crouton padding. + # Input width and height are padded to a multiple of croutons. + # NOTE: Input layout is always assumed to be nhwc-8h2w32c2w. Only the output layout can be + # different. + pad_before_h, pad_before_w = padding[:2] + pad_after_h, pad_after_w = padding[2:] + padded_input_height = ((input_shape[1] + pad_before_h + pad_after_h + 7) // 8) * 8 + padded_input_width = ((input_shape[2] + pad_before_w + pad_after_w + 3) // 4) * 4 + return [input_shape[0], padded_input_height, padded_input_width, input_shape[3]] + + @tvm.testing.fixture + def input_np_padded(self, input_np, input_shape, input_shape_padded, padding): + pad_before_h, pad_before_w = padding[:2] + pad_after_h = ( + input_shape_padded[1] - input_shape[1] - pad_before_h + ) # pad_after for height with crouton padding + pad_after_w = ( + input_shape_padded[2] - input_shape[2] - pad_before_w + ) # pad_after for width with crouton padding + input_padded = np.pad( + input_np, + ((0, 0), (pad_before_h, pad_after_h), (pad_before_w, pad_after_w), (0, 0)), + "constant", + ) + return input_padded + + @tvm.testing.requires_hexagon + def test_avg_pool2d_slice( + self, + use_te_sched, + stride, + kernel, + dtype, + dilation, + padding, + count_include_pad, + input_layout, + output_layout, + output_shape, + input_shape, + input_shape_padded, + input_np, + input_np_padded, + transformed_input_np_padded, + transformed_expected_output_np, + expected_output_np, + hexagon_session, + ): + + target_hexagon = tvm.target.hexagon("v69") Review Comment: AFAIK, TVM's Hexagon CI has only tested v68 code in the past. Is there any possibility that specifying v69 here will break CI or require some newer version of the Hexagon SDK? -- 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: commits-unsubscr...@tvm.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
