From a1f107072b4694a0be088090762852c16b0abe26 Mon Sep 17 00:00:00 2001 From: Yanzhan Yang Date: Mon, 24 Jun 2019 18:02:34 +0800 Subject: [PATCH] 1.add last type sequence pool. 2.enable lod for auto debug tools. (#1700) --- src/common/types.h | 1 + .../kernel/arm/sequence_pool_kernel.cpp | 18 ++++++++ src/pass/memory_optimize.cpp | 8 ++++ test/net/test_net.cpp | 41 +++++++++++++++++-- test/test_include.h | 1 + tools/python/fluidtools/run.py | 36 ++++++++++++++-- 6 files changed, 98 insertions(+), 7 deletions(-) diff --git a/src/common/types.h b/src/common/types.h index 8e793e959b..4d9f9b3e31 100644 --- a/src/common/types.h +++ b/src/common/types.h @@ -109,6 +109,7 @@ enum PoolingType { AVG = 1, SUM = 2, FIRST = 3, + LAST = 4, }; enum PowerMode { diff --git a/src/operators/kernel/arm/sequence_pool_kernel.cpp b/src/operators/kernel/arm/sequence_pool_kernel.cpp index 2be2accf58..db1939d4d0 100644 --- a/src/operators/kernel/arm/sequence_pool_kernel.cpp +++ b/src/operators/kernel/arm/sequence_pool_kernel.cpp @@ -163,6 +163,22 @@ void SequencePoolImpl(const framework::LoDTensor &input, } } +template <> +void SequencePoolImpl(const framework::LoDTensor &input, + framework::LoDTensor *output) { + const float *input_ptr = input.data(); + float *output_ptr = output->mutable_data(); + const auto &lod = input.lod()[0]; + int64_t width = input.numel() / input.dims()[0]; + + for (int i = 0; i < static_cast(lod.size()) - 1; ++i) { + int64_t seq_len = static_cast(lod[i + 1] - lod[i]); + const float *in_ptr = input_ptr + seq_len * width; + float *out_ptr = output_ptr + i * width; + memcpy(out_ptr, in_ptr - width, width * sizeof(float)); + } +} + template class SequencePoolKernel : public framework::OpKernelBase> { @@ -179,6 +195,8 @@ class SequencePoolKernel SequencePoolImpl(*input, output); } else if (param.pool_type_ == "FIRST") { SequencePoolImpl(*input, output); + } else if (param.pool_type_ == "LAST") { + SequencePoolImpl(*input, output); } else if (param.pool_type_ == "SUM") { SequencePoolImpl(*input, output); } else { diff --git a/src/pass/memory_optimize.cpp b/src/pass/memory_optimize.cpp index cc754491fa..96a610151c 100644 --- a/src/pass/memory_optimize.cpp +++ b/src/pass/memory_optimize.cpp @@ -60,6 +60,7 @@ void MemoryOptPass::operator()(const framework::ProgramDesc *program, std::stack empty_var_nodes; analysis_nodes_.swap(empty_var_nodes); + std::vector fetch_var_nodes; for (const auto &op : block->Ops()) { DLOG << "op_desc->Type(): " << op->Type(); for (const auto &outputs : op->GetOutputs()) { @@ -77,6 +78,9 @@ void MemoryOptPass::operator()(const framework::ProgramDesc *program, DLOG << "input: " << input; VarNode *node = CreateNode(input); analysis_nodes_.push(node); + if (op->Type() == "fetch") { + fetch_var_nodes.push_back(node); + } } } } @@ -91,6 +95,10 @@ void MemoryOptPass::operator()(const framework::ProgramDesc *program, } } + for (const auto &node : fetch_var_nodes) { + analysis_nodes_.push(node); + } + // apply optimize while (!analysis_nodes_.empty()) { auto *node = analysis_nodes_.top(); diff --git a/test/net/test_net.cpp b/test/net/test_net.cpp index 24a5002111..be7c21db7b 100644 --- a/test/net/test_net.cpp +++ b/test/net/test_net.cpp @@ -46,6 +46,19 @@ void test(int argc, char *argv[]) { } arg_index += dim_count; + bool is_lod = std::stoi(argv[arg_index]) == 1; + arg_index++; + paddle_mobile::framework::LoD lod{{}}; + if (is_lod) { + int lod_count = std::stoi(argv[arg_index]); + arg_index++; + for (int i = 0; i < lod_count; i++) { + int dim = std::stoi(argv[arg_index + i]); + lod[0].push_back(dim); + } + arg_index += lod_count; + } + int var_count = std::stoi(argv[arg_index]); arg_index++; int sample_step = std::stoi(argv[arg_index]); @@ -74,15 +87,33 @@ void test(int argc, char *argv[]) { } in.close(); + paddle_mobile::framework::LoDTensor input_tensor; + if (is_lod) { + input_tensor.Resize(paddle_mobile::framework::make_ddim(dims)); + input_tensor.set_lod(lod); + auto *tensor_data = input_tensor.mutable_data(); + for (int i = 0; i < size; i++) { + tensor_data[i] = input_data[i]; + } + } + // 预热10次 for (int i = 0; i < 10; i++) { - auto out = paddle_mobile.Predict(input_data, dims); + if (is_lod) { + auto out = paddle_mobile.Predict(input_tensor); + } else { + auto out = paddle_mobile.Predict(input_data, dims); + } } // 测速 auto time3 = time(); for (int i = 0; i < 50; i++) { - auto out = paddle_mobile.Predict(input_data, dims); + if (is_lod) { + auto out = paddle_mobile.Predict(input_tensor); + } else { + auto out = paddle_mobile.Predict(input_data, dims); + } } auto time4 = time(); std::cout << "auto-test" @@ -90,7 +121,11 @@ void test(int argc, char *argv[]) { << std::endl; // 测试正确性 - auto out = paddle_mobile.Predict(input_data, dims); + if (is_lod) { + auto out = paddle_mobile.Predict(input_tensor); + } else { + auto out = paddle_mobile.Predict(input_data, dims); + } for (auto var_name : var_names) { auto out = paddle_mobile.Fetch(var_name); auto len = out->numel(); diff --git a/test/test_include.h b/test/test_include.h index 4728a46933..7f45d6e2c4 100644 --- a/test/test_include.h +++ b/test/test_include.h @@ -22,6 +22,7 @@ limitations under the License. */ #include "common/enforce.h" #include "common/log.h" #include "executor_for_test.h" +#include "framework/ddim.h" #include "framework/lod_tensor.h" #include "framework/operator.h" #include "framework/program/block_desc.h" diff --git a/tools/python/fluidtools/run.py b/tools/python/fluidtools/run.py index 8eb67b3c38..e7ac827b99 100644 --- a/tools/python/fluidtools/run.py +++ b/tools/python/fluidtools/run.py @@ -11,6 +11,7 @@ checked_model_path = "checked_model" feed_path = "feeds" output_path = "outputs" diff_threshold = 0.01 +is_lod = True np.set_printoptions(linewidth=150) @@ -59,7 +60,7 @@ def load_model(model_path): prog, feeds, fetches = load_model(model_path) # 强制要求所有张量的形状，在model和params中一致，并重新保存模型 -def resave_model(): +def resave_model(feed_kv): ops = prog.current_block().ops vars = prog.current_block().vars # 强制所有var为可持久化 @@ -70,7 +71,7 @@ def resave_model(): if not v.persistable: v.persistable = True p_names.append(name) - outputs = run_model() + outputs = run_model(feed_kv=feed_kv) has_found_wrong_shape = False # 修正每个var的形状 for name in vars: @@ -121,12 +122,14 @@ def save_feed_kv(feed_kv): last_feed_var_name = None last_feed_file_name = None +last_feed_var_lod = None # 加载feed的key-value对 def load_feed_kv(): if not os.path.exists(feed_path): return None global last_feed_var_name global last_feed_file_name + global last_feed_var_lod feed_kv = {} pp_yellow(dot + dot + " checking feed info") pp_green("feed data is saved into directory 【{}】".format(feed_path), 1) @@ -146,7 +149,23 @@ def load_feed_kv(): if len(data) != expected_len: return None data = data.reshape(feed_shape).astype("float32") - feed_kv[feed_name] = data + + if is_lod: + data = data.reshape((1, *feed_shape)).astype("float32") + tensor = fluid.LoDTensor() + seq_lens = [len(seq) for seq in data] + cur_len = 0 + lod = [cur_len] + for l in seq_lens: + cur_len += 1 + lod.append(cur_len) + data = data.reshape(feed_shape) + tensor.set(data, fluid.CPUPlace()) + tensor.set_lod([lod]) + last_feed_var_lod = lod + feed_kv[feed_name] = tensor + else: + feed_kv[feed_name] = data return feed_kv # 运行模型 @@ -204,6 +223,8 @@ def save_all_op_output(feed_kv=None): var_name = name if "tmp" in name: break + if "sequence_pool" in name: + continue try: data = get_var_data(var_name, feed_kv=feed_kv).flatten().tolist() sample = tensor_sample(data) @@ -311,7 +332,7 @@ def main(): pp_tab("fluid output : {}".format(outputs), 1) # 重新保存模型 pp_yellow(dot + dot + " checking model correctness") - resave_model() + resave_model(feed_kv=feed_kv) # 输出所有中间结果 pp_yellow(dot + dot + " checking output result of every op") save_all_op_output(feed_kv=feed_kv) @@ -328,6 +349,13 @@ def main(): args = str(len(last_feed_var_shape)) for dim in last_feed_var_shape: args += " " + str(dim) + if is_lod: + args += " 1" + args += " " + str(len(last_feed_var_lod)) + for dim in last_feed_var_lod: + args += " " + str(dim) + else: + args += " 0" args += " " + str(len(output_var_cache)) args += " " + str(sample_step) for var_name in output_var_cache.keys(): -- GitLab