forked from apache/tvm
-
Notifications
You must be signed in to change notification settings - Fork 30
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Move SimplifyConvPad to a new pass and don't enable it by default (ap…
…ache#7603) * Move SimplifyConvPad to a new pass and don't enable it by default * rename pass * move files * fix lint * adjust test tolerance
- Loading branch information
Showing
5 changed files
with
322 additions
and
192 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,207 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
|
||
| /*! | ||
| * \file src/relay/transforms/fold_explicit_padding.cc | ||
| * \brief A pass for folding explicit pads into other ops. | ||
| */ | ||
|
|
||
| #include <tvm/relay/dataflow_matcher.h> | ||
| #include <tvm/relay/expr.h> | ||
| #include <tvm/relay/expr_functor.h> | ||
| #include <tvm/relay/transform.h> | ||
| #include <tvm/support/logging.h> | ||
|
|
||
| #include "../op/tensor/transform.h" | ||
| #include "pattern_utils.h" | ||
|
|
||
| namespace tvm { | ||
| namespace relay { | ||
|
|
||
| /*! | ||
| * \brief SimplifyConvPad matches a pad followed by a conv/convtranspose/pool/etc | ||
| * with a pad attribute and merges the padding into the kernel. | ||
| */ | ||
| class SimplifyConvPad { | ||
| public: | ||
| DFPattern pattern() const { return pattern_; } | ||
|
|
||
| SimplifyConvPad() { | ||
| x_ = IsWildcard(); | ||
| w_ = IsWildcard(); | ||
| pad_ = IsOp("nn.pad")({x_}); | ||
| conv1d_ = IsOp("nn.conv1d"); | ||
| conv2d_ = IsOp("nn.conv2d"); | ||
| conv3d_ = IsOp("nn.conv3d"); | ||
| conv_ = (conv1d_ || conv2d_ || conv3d_)({pad_, w_}); | ||
| pattern_ = conv_; | ||
| } | ||
|
|
||
| template <typename T> | ||
| Attrs MakeConvAttrs(const T* old_attrs, const Array<PrimExpr> padding) const { | ||
| ICHECK(old_attrs); | ||
| ICHECK(padding.size() == old_attrs->padding.size()) | ||
| << "Number of dimensions to pad and convolution padding attributes should have the same " | ||
| "extent"; | ||
|
|
||
| auto new_attrs = make_object<T>(); | ||
| Array<PrimExpr> combined_padding; | ||
| for (size_t i = 0; i < padding.size(); ++i) { | ||
| combined_padding.push_back(padding[i] + old_attrs->padding[i]); | ||
| } | ||
| new_attrs->strides = old_attrs->strides; | ||
| new_attrs->padding = combined_padding; | ||
| new_attrs->dilation = old_attrs->dilation; | ||
| new_attrs->groups = old_attrs->groups; | ||
| new_attrs->channels = old_attrs->channels; | ||
| new_attrs->kernel_size = old_attrs->kernel_size; | ||
| new_attrs->data_layout = old_attrs->data_layout; | ||
| new_attrs->kernel_layout = old_attrs->kernel_layout; | ||
| new_attrs->out_layout = old_attrs->out_layout; | ||
| new_attrs->out_dtype = old_attrs->out_dtype; | ||
| return Attrs(new_attrs); | ||
| } | ||
|
|
||
| template <typename T> | ||
| Attrs GetAttrs(const PadAttrs* param, const T* attrs) const { | ||
| ICHECK(param); | ||
| ICHECK(attrs); | ||
| ICHECK(attrs->data_layout.size() == param->pad_width.size()) | ||
| << "Data Layout and padding attributes should have the same extent"; | ||
|
|
||
| std::string data_layout = attrs->data_layout; | ||
| std::set<char> image_dims({'H', 'W', 'D'}); | ||
| Array<PrimExpr> padding; | ||
| // If we're padding a non-spatial dimension, don't simplify | ||
| // Convolution can only pad on spatial axes | ||
| for (size_t i = 0; i < param->pad_width.size(); ++i) { | ||
| if (!image_dims.count(data_layout[i])) { | ||
| for (size_t j = 0; j < param->pad_width[i].size(); ++j) { | ||
| if (param->pad_width[i][j] != 0) { | ||
| return Attrs(); | ||
| } | ||
| } | ||
| } | ||
| } | ||
| for (size_t j = 0; j < param->pad_width[0].size(); ++j) { | ||
| for (size_t i = 0; i < param->pad_width.size(); ++i) { | ||
| if (image_dims.count(data_layout[i])) { | ||
| padding.push_back(param->pad_width[i][j]); | ||
| } | ||
| } | ||
| } | ||
|
|
||
| return MakeConvAttrs(attrs, padding); | ||
| } | ||
|
|
||
| Expr callback(const Expr& pre, const Expr& post, | ||
| const Map<DFPattern, Array<Expr>>& node_map) const { | ||
| const CallNode* call_node = post.as<CallNode>(); | ||
| ICHECK(call_node); | ||
| auto pad = node_map[pad_][0]; | ||
| const CallNode* pad_node = pad.as<CallNode>(); | ||
| ICHECK(pad_node); | ||
| const PadAttrs* param = pad_node->attrs.as<PadAttrs>(); | ||
| ICHECK(param); | ||
| if (param->pad_mode == "constant" && param->pad_value == 0.0) { | ||
| Attrs attrs; | ||
| if (node_map.count(conv1d_)) { | ||
| attrs = GetAttrs(param, call_node->attrs.as<Conv1DAttrs>()); | ||
| } else if (node_map.count(conv2d_)) { | ||
| attrs = GetAttrs(param, call_node->attrs.as<Conv2DAttrs>()); | ||
| } else if (node_map.count(conv3d_)) { | ||
| attrs = GetAttrs(param, call_node->attrs.as<Conv3DAttrs>()); | ||
| } else { | ||
| return post; | ||
| } | ||
| if (!attrs.defined()) { | ||
| return post; | ||
| } | ||
| auto x = node_map[x_][0]; | ||
| auto w = node_map[w_][0]; | ||
| return Call(call_node->op, {x, w}, attrs, call_node->type_args, call_node->span); | ||
| } | ||
| return post; | ||
| } | ||
|
|
||
| private: | ||
| /*! \brief Pattern for rewriting */ | ||
| DFPattern pattern_; | ||
| /*! \brief Pattern input */ | ||
| DFPattern x_; | ||
| /*! \brief Pattern input weight */ | ||
| DFPattern w_; | ||
| /*! \brief Pattern pad */ | ||
| DFPattern pad_; | ||
| /*! \brief Pattern conv */ | ||
| DFPattern conv_; | ||
| DFPattern conv1d_; | ||
| DFPattern conv2d_; | ||
| DFPattern conv3d_; | ||
| }; | ||
|
|
||
| class SimplifyExplicitPadding { | ||
| public: | ||
| explicit SimplifyExplicitPadding(IRModule mod) : mod_(mod) { | ||
| CreateCallback(SimplifyConvPad()); | ||
| // TODO(mbrookhart): ConvTranspose(Pad(x)), Pool(Pad(x)) | ||
| } | ||
| template <typename T> | ||
| void CreateCallback(const T& pattern) { | ||
| auto func = [pattern](TVMArgs args, TVMRetValue* rv) { | ||
| Expr pre = args[0]; | ||
| Expr post = args[1]; | ||
| Map<DFPattern, Array<Expr>> node_map = args[2]; | ||
| *rv = pattern.callback(pre, post, node_map); | ||
| }; | ||
| callbacks_.push_back(DFPatternCallback(pattern.pattern(), PackedFunc(func), true)); | ||
| } | ||
|
|
||
| Expr Simplify(const Expr& expr) { return RewritePatterns(callbacks_, expr, mod_); } | ||
|
|
||
| private: | ||
| IRModule mod_; | ||
| /*! \brief Callbacks for expr simplification */ | ||
| Array<DFPatternCallback> callbacks_; | ||
| }; | ||
|
|
||
| /*! | ||
| * \brief ImplicitPadding finds explict padding before an op that can | ||
| * support implicit padding and fuses them. | ||
| */ | ||
| Expr FoldExplicitPadding(const Expr& expr, const IRModule& mod) { | ||
| return SimplifyExplicitPadding(mod).Simplify(expr); | ||
| } | ||
|
|
||
| namespace transform { | ||
|
|
||
| Pass FoldExplicitPadding() { | ||
| runtime::TypedPackedFunc<Function(Function, IRModule, PassContext)> pass_func = | ||
| [=](Function f, IRModule m, PassContext pc) { | ||
| return Downcast<Function>(FoldExplicitPadding(f, m)); | ||
| }; | ||
| return CreateFunctionPass(pass_func, 0, " FoldExplicitPadding", {"InferType"}); | ||
| } | ||
|
|
||
| TVM_REGISTER_GLOBAL("relay._transform.FoldExplicitPadding").set_body_typed(FoldExplicitPadding); | ||
|
|
||
| } // namespace transform | ||
|
|
||
| } // namespace relay | ||
| } // namespace tvm |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.