| # 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 |
| |
| pytest.importorskip("ethosu.vela") |
| |
| import tvm |
| from tvm import relay |
| from tvm.relay.testing import run_opt_pass |
| from tvm.relay.backend.contrib.ethosu.tir import spec |
| from tvm.relay.backend.contrib.ethosu.tir.compiler import _lower_to_tir |
| from .infra import make_ethosu_pooling, get_pooling_args |
| |
| |
| def _create_serial_pooling( |
| ifm_shape, |
| ofm_channels, |
| ifm_layout, |
| ofm_layout, |
| pool_shape, |
| pooling_type, |
| strides, |
| padding, |
| activation="NONE", |
| rounding_mode="TFL", |
| upscale="NONE", |
| ofm_dtype="int8", |
| ): |
| upscale_factor = 2 if upscale != "NONE" else 1 |
| if ifm_layout == "NHWC": |
| ifm_stride_c = 1 |
| ifm_stride_w = ifm_shape[3] |
| ifm_stride_h = ifm_shape[2] * ifm_shape[3] |
| ofm_height = ( |
| ifm_shape[1] * upscale_factor - pool_shape[0] + padding[0] + padding[2] |
| ) // strides[0] + 1 |
| ofm_width = ( |
| ifm_shape[2] * upscale_factor - pool_shape[1] + padding[1] + padding[3] |
| ) // strides[1] + 1 |
| else: |
| ifm_stride_w = 16 |
| ifm_stride_c = 16 * ifm_shape[3] if ofm_channels >= 16 else 1 |
| ifm_stride_h = 16 * ifm_shape[2] * ifm_shape[3] |
| ofm_height = ( |
| ifm_shape[1] * upscale_factor - pool_shape[0] + padding[0] + padding[2] |
| ) // strides[0] + 1 |
| ofm_width = ( |
| ifm_shape[3] * upscale_factor - pool_shape[1] + padding[1] + padding[3] |
| ) // strides[1] + 1 |
| |
| if ofm_layout == "NHWC": |
| ofm_stride_c = 1 |
| ofm_stride_w = ofm_channels if ofm_width > 1 else 1 |
| ofm_stride_h = ofm_channels * ofm_width if ofm_height > 1 else 1 |
| else: |
| ofm_stride_w = 16 |
| ofm_stride_c = 16 * ofm_width if ofm_channels >= 16 else 1 |
| ofm_stride_h = 16 * ofm_width * ((ofm_channels - 1) // 16 + 1) |
| |
| ifm_channels = ofm_channels if pooling_type != "SUM" else ifm_shape[-1] |
| |
| return spec.SerialPooling( |
| ifm=spec.SerialFeatureMap( |
| data_type="int8", |
| height=ifm_shape[1], |
| width=ifm_shape[2] if ifm_layout == "NHWC" else ifm_shape[3], |
| channels=ifm_channels, |
| tile_height_0=ifm_shape[1], |
| tile_height_1=0, |
| tile_width_0=ifm_shape[2] if ifm_layout == "NHWC" else ifm_shape[3], |
| tile_address_0=0, |
| tile_address_1=0, |
| tile_address_2=0, |
| tile_address_3=0, |
| scale=1.0, |
| zero_point=0, |
| layout=ifm_layout, |
| stride_h=ifm_stride_h, |
| stride_w=ifm_stride_w, |
| stride_c=ifm_stride_c, |
| ), |
| ofm=spec.SerialFeatureMap( |
| data_type=ofm_dtype, |
| height=ofm_height, |
| width=ofm_width, |
| channels=ofm_channels, |
| tile_height_0=ofm_height, |
| tile_height_1=0, |
| tile_width_0=ofm_width, |
| tile_address_0=0, |
| tile_address_1=0, |
| tile_address_2=0, |
| tile_address_3=0, |
| scale=1.0, |
| zero_point=0, |
| layout=ofm_layout, |
| stride_h=ofm_stride_h, |
| stride_w=ofm_stride_w, |
| stride_c=ofm_stride_c, |
| ), |
| pooling_type=pooling_type, |
| pool_shape=spec.SerialKernel( |
| width=pool_shape[1], |
| height=pool_shape[0], |
| stride_w=strides[1], |
| stride_h=strides[0], |
| dilation_w=1, |
| dilation_h=1, |
| ), |
| padding=spec.SerialPadding( |
| top=padding[0], left=padding[1], bottom=padding[2], right=padding[3] |
| ), |
| activation=spec.SerialActivation( |
| op=activation, |
| clip_min=10 if activation == "CLIP" else 0, |
| clip_max=100 if activation == "CLIP" else 0, |
| ), |
| rounding_mode=rounding_mode, |
| upscale=upscale, |
| block_config=spec.SerialBlockConfig(0, 0, 0), |
| ) |
| |
| |
| @pytest.mark.parametrize( |
| "ifm_shape, ofm_channels, ifm_layout, ofm_layout, rounding_mode, upscale", |
| [ |
| ((1, 5, 9, 3), 3, "NHWC", "NHWC", "TFL", "NONE"), |
| ((1, 8, 3, 9, 16), 40, "NHCWB16", "NHCWB16", "NATURAL", "NONE"), |
| ((1, 8, 3, 9, 16), 40, "NHCWB16", "NHWC", "TRUNCATE", "ZEROS"), |
| ((1, 8, 9, 40), 40, "NHWC", "NHCWB16", "TFL", "ZEROS"), |
| ((1, 8, 9, 8), 8, "NHWC", "NHCWB16", "TFL", "NEAREST"), |
| ((1, 5, 9, 3), 3, "NHWC", "NHWC", "TFL", "NEAREST"), |
| ], |
| ) |
| @pytest.mark.parametrize("pooling_type", ["AVG", "MAX"]) |
| @pytest.mark.parametrize("activation", ["NONE", "CLIP"]) |
| def test_avg_max_pooling_single( |
| ifm_shape, |
| ofm_channels, |
| ifm_layout, |
| ofm_layout, |
| pooling_type, |
| activation, |
| rounding_mode, |
| upscale, |
| ): |
| pool_shape = (3, 2) |
| strides = (1, 2) |
| |
| # When strides are not (1, 1) it is possible to create invalid |
| # padding configurations. It is possible to construct a pooling |
| # operation with invalid padding, but the compiler will account |
| # for this and adjust the padding accordingly, leading to a |
| # mismatch between the expected and actual result. Therefore, |
| # hardcoded padding values are used for each case. |
| padding = (1, 1, 1, 0) if upscale == "NONE" else (0, 0, 0, 0) |
| |
| dtype = "int8" |
| |
| ifm = relay.var("ifm", shape=ifm_shape, dtype=dtype) |
| pooling = make_ethosu_pooling( |
| ifm, |
| pooling_type, |
| pool_shape, |
| ofm_channels, |
| dtype, |
| strides, |
| padding, |
| activation, |
| ifm_layout, |
| ofm_layout, |
| rounding_mode, |
| upscale, |
| ) |
| func = relay.Function(relay.analysis.free_vars(pooling), pooling) |
| func = run_opt_pass(func, relay.transform.InferType()) |
| mod, _ = _lower_to_tir(func) |
| data = [] |
| |
| def _visit(stmt): |
| if isinstance(stmt, tvm.tir.Call): |
| data.append(get_pooling_args(stmt)) |
| |
| tvm.tir.stmt_functor.post_order_visit(mod["main"].body, _visit) |
| |
| serial_pooling = _create_serial_pooling( |
| ifm_shape, |
| ofm_channels, |
| ifm_layout, |
| ofm_layout, |
| pool_shape, |
| pooling_type, |
| strides, |
| padding, |
| activation, |
| rounding_mode, |
| upscale, |
| ) |
| assert data[0] == ["ethosu_pooling"] + list(serial_pooling) |
| |
| |
| @pytest.mark.parametrize( |
| "ifm_shape, ofm_layout, rounding_mode", |
| [ |
| ((1, 5, 9, 3), "NHWC", "TFL"), |
| ((1, 8, 9, 40), "NHCWB16", "TFL"), |
| ((1, 8, 9, 8), "NHCWB16", "TRUNCATE"), |
| ((1, 5, 9, 3), "NHWC", "NATURAL"), |
| ], |
| ) |
| @pytest.mark.parametrize("activation", ["NONE", "CLIP"]) |
| def test_sum_pooling_single( |
| ifm_shape, |
| ofm_layout, |
| activation, |
| rounding_mode, |
| ): |
| ifm = relay.var("ifm", shape=ifm_shape, dtype="int8") |
| pooling = make_ethosu_pooling( |
| ifm=ifm, |
| pooling_type="SUM", |
| pool_shape=(1, 1), |
| ofm_channels=1, |
| ofm_dtype="int32", |
| strides=(1, 1), |
| padding=(0, 0, 0, 0), |
| activation=activation, |
| ofm_layout=ofm_layout, |
| rounding_mode=rounding_mode, |
| ) |
| func = relay.Function(relay.analysis.free_vars(pooling), pooling) |
| func = run_opt_pass(func, relay.transform.InferType()) |
| mod, _ = _lower_to_tir(func) |
| data = [] |
| |
| def _visit(stmt): |
| if isinstance(stmt, tvm.tir.Call): |
| data.append(get_pooling_args(stmt)) |
| |
| tvm.tir.stmt_functor.post_order_visit(mod["main"].body, _visit) |
| |
| serial_pooling = _create_serial_pooling( |
| ifm_shape=ifm_shape, |
| ofm_channels=1, |
| ifm_layout="NHWC", |
| ofm_layout=ofm_layout, |
| pool_shape=(1, 1), |
| pooling_type="SUM", |
| strides=(1, 1), |
| padding=(0, 0, 0, 0), |
| activation=activation, |
| rounding_mode=rounding_mode, |
| ofm_dtype="int32", |
| ) |
| assert data[0] == ["ethosu_pooling"] + list(serial_pooling) |
| |
| |
| def test_correct_stride_with_multiple_pooling(): |
| """Testing a specific case of two pooling operations with NHWC inputs/outputs |
| but a NHCWB16 intermediate tensor. This lead to elements being accessed in the |
| wrong order by the NPU, due to incorrect stride values being calculated.""" |
| |
| ifm_shape = (1, 4, 4, 8) |
| ofm_channels = 8 |
| pooling_type = "MAX" |
| pool_shape = (1, 1) |
| strides = (1, 1) |
| padding = (0, 0, 0, 0) |
| dtype = "int8" |
| |
| ifm = relay.var("ifm", shape=ifm_shape, dtype=dtype) |
| op = make_ethosu_pooling( |
| ifm, |
| pooling_type, |
| pool_shape, |
| ofm_channels, |
| dtype, |
| strides, |
| padding, |
| ifm_layout="NHWC", |
| ofm_layout="NHCWB16", |
| ) |
| op = make_ethosu_pooling( |
| op, |
| pooling_type, |
| pool_shape, |
| ofm_channels, |
| dtype, |
| strides, |
| padding, |
| ifm_layout="NHCWB16", |
| ofm_layout="NHWC", |
| ) |
| func = relay.Function(relay.analysis.free_vars(op), op) |
| func = run_opt_pass(func, relay.transform.InferType()) |
| mod, _ = _lower_to_tir(func) |
| |
| data = [] |
| |
| def _visit(stmt): |
| if isinstance(stmt, tvm.tir.Call): |
| data.append(get_pooling_args(stmt)) |
| |
| tvm.tir.stmt_functor.post_order_visit(mod["main"].body, _visit) |
| |
| serial_pooling_1 = _create_serial_pooling( |
| [1, 4, 4, 8], |
| 8, |
| "NHWC", |
| "NHCWB16", |
| pool_shape, |
| pooling_type, |
| strides, |
| padding, |
| ) |
| serial_pooling_2 = _create_serial_pooling( |
| [1, 4, 1, 4, 16], |
| 8, |
| "NHCWB16", |
| "NHWC", |
| pool_shape, |
| pooling_type, |
| strides, |
| padding, |
| ) |
| |
| assert data[0] == ["ethosu_pooling"] + list(serial_pooling_1) |
| assert data[1] == ["ethosu_pooling"] + list(serial_pooling_2) |
| |
| |
| if __name__ == "__main__": |
| tvm.testing.main() |
