diff --git a/paddle/fluid/platform/device/ipu/ipu_compiler.cc b/paddle/fluid/platform/device/ipu/ipu_compiler.cc index 7ae3b2303decd7b35409a40bcadda46eee9184b0..463803dd03f1059f8f6918a7e3972206a0da954e 100644 --- a/paddle/fluid/platform/device/ipu/ipu_compiler.cc +++ b/paddle/fluid/platform/device/ipu/ipu_compiler.cc @@ -185,12 +185,9 @@ void Compiler::RegisterOpFunc() { auto debug_context = BuildDebugContext(op_desc); \ auto aiGraphcoreOpset = builder_->aiGraphcoreOpset1(); \ auto aiOnnxOpset = builder_->aiOnnxOpset11(); \ - PushNameScope(op_desc); \ + NameScopeHelper ns_helper(op_desc, builder_.get()); \ auto output_ids = OnnxImpl(inputs Args, debug_context); \ - PopNameScope(op_desc); \ - SetIpuIndexStage(output_ids, op_desc); \ - SetAMPAttributes(output_ids, op_desc); \ - SetSerializeAttributes(output_ids, op_desc); \ + PostLower(output_ids, op_desc); \ InsertTensors(output_names, output_ids); \ }}, // NOLINT #include "paddle/fluid/platform/device/ipu/supported_ops_autogen.h" @@ -273,10 +270,9 @@ void Compiler::LowerConstants(const Scope* scope) { popart::TensorInfo tensor_info(PdDataType2PopartType(tensor->dtype()), shape); const_data.reset(new popart::ConstVoidData(tensor->data(), tensor_info)); - PushNameScope(op_desc); + NameScopeHelper ns_helper(op_desc, builder_.get()); popart::TensorId result = builder_->aiOnnxOpset11().constant(*const_data); - PopNameScope(op_desc); - SetIpuIndexStage(result, op_desc); + PostLower(result, op_desc); resources_->tensors.emplace(tensor_name, result); } } @@ -285,42 +281,42 @@ void Compiler::LowerConstants(const Scope* scope) { void Compiler::LowerWeights(const Scope* scope) { VLOG(10) << "enter Compiler::LowerWeights"; - // at this step, the graph doesn't contains optimizer related states + // At this step, the graph doesn't contains optimizer related states for (auto id : graph_helper_->sorted_vars_id) { auto* node = graph_helper_->nodes_id_map[id]; - if (node->IsVar() && !node->IsCtrlVar() && node->Var()) { - if (node->Var()->Persistable() && node->inputs.empty()) { - auto var_name = node->Var()->Name(); - if (resources_->tensors.count(var_name) != 0) { - VLOG(10) << "found existed one, skip lowering Weight: " << var_name; - continue; - } - if (var_name.rfind("learning_rate", 0) == 0) { - VLOG(10) << "skip learning_rate_var: " << var_name; - continue; - } - VLOG(10) << "lowering weight: " << var_name; - - auto var = scope->FindVar(var_name); - if (var) { - auto tensor = var->Get(); - auto dtype = PdDataType2PopartType(tensor.dtype()); - auto shape = std::vector(); - for (size_t i = 0; i < tensor.dims().size(); ++i) { - shape.push_back(tensor.dims().at(i)); - } - popart::TensorInfo tensor_info(dtype, shape); - popart::ConstVoidData const_data{tensor.data(), tensor_info}; - if (!node->outputs.empty()) { - auto op_node = node->outputs[0]; - PushNameScope(op_node->Op()); - popart::TensorId result = - builder_->addInitializedInputTensor(const_data, var_name); - PopNameScope(op_node->Op()); - resources_->tensors.emplace(var_name, result); - resources_->weights.push_back(var_name); - } - } + // Weights are var node and Persistable + if (node->IsVar() && !node->IsCtrlVar() && node->Var() && + node->Var()->Persistable()) { + // Weights are Parameter in training mode + if (ipu_strategy_->is_training && !node->Var()->IsParameter()) { + continue; + } + auto var_name = node->Var()->Name(); + // Some op has same input and output tensor, like batchnorm + if (resources_->tensors.count(var_name) != 0) { + VLOG(10) << "found existed one, skip lowering Weight: " << var_name; + continue; + } + VLOG(10) << "lowering weight: " << var_name; + auto var = scope->FindVar(var_name); + PADDLE_ENFORCE_NOT_NULL( + var, platform::errors::NotFound("Tensor %s is not found in the scope", + var_name)); + auto tensor = var->Get(); + auto dtype = PdDataType2PopartType(tensor.dtype()); + auto shape = std::vector(); + for (size_t i = 0; i < tensor.dims().size(); ++i) { + shape.push_back(tensor.dims().at(i)); + } + popart::TensorInfo tensor_info(dtype, shape); + popart::ConstVoidData const_data{tensor.data(), tensor_info}; + if (!node->outputs.empty()) { + auto op_node = node->outputs[0]; + NameScopeHelper ns_helper(op_node->Op(), builder_.get()); + popart::TensorId result = + builder_->addInitializedInputTensor(const_data, var_name); + resources_->tensors.emplace(var_name, result); + resources_->weights.push_back(var_name); } } } @@ -341,10 +337,9 @@ void Compiler::LowerBody() { } else if (op_type == "popart_checkpointoutput") { auto inputs = GetOpInputs(op_desc); auto outputs = GetOpOutputs(op_desc); - PushNameScope(op_desc); + NameScopeHelper ns_helper(op_desc, builder_.get()); auto output_ids = builder_->checkpointOutput(inputs); - PopNameScope(op_desc); - SetIpuIndexStage(output_ids, op_desc); + PostLower(output_ids, op_desc); InsertTensors(outputs, output_ids); } else if (op_type == "popart_custom_op") { auto inputs = GetOpInputs(op_desc); @@ -359,12 +354,11 @@ void Compiler::LowerBody() { BOOST_GET_CONST(std::string, op_desc->GetAttr("__op_type")); VLOG(10) << "Build graph from custom op: " << __op_type; auto it = custom_ops_.find(__op_type); - PushNameScope(op_desc); + NameScopeHelper ns_helper(op_desc, builder_.get()); auto output_ids = builder_->customOp(it->second.popart_op, it->second.popart_op.version, inputs, outputs.size(), attributes, debug_context); - PopNameScope(op_desc); - SetIpuIndexStage(output_ids, op_desc); + PostLower(output_ids, op_desc); InsertTensors(outputs, output_ids); } else if (op_type == "popart_printtensor") { auto inputs = GetOpInputs(op_desc); @@ -373,11 +367,10 @@ void Compiler::LowerBody() { auto print_gradient = BOOST_GET_CONST(int64_t, op_desc->GetAttr("print_gradient")); auto title = BOOST_GET_CONST(std::string, op_desc->GetAttr("title")); - PushNameScope(op_desc); + NameScopeHelper ns_helper(op_desc, builder_.get()); auto output_ids = builder_->aiGraphcoreOpset1().printtensor( inputs, print_gradient, debug_context, title); - PopNameScope(op_desc); - SetIpuIndexStage(output_ids, op_desc); + PostLower(output_ids, op_desc); InsertTensors(outputs, output_ids); } else { auto itr = name_function_.find(op_type); @@ -625,12 +618,13 @@ void Compiler::InsertTensors(const std::vector& output_names, resources_->tensors.emplace(output_names[0], tensor_id); } -void Compiler::SetIpuIndexStage(const std::vector& tensor_ids, - const OpDesc* op_desc) { - VLOG(10) << "enter Compiler::SetIpuIndexStage"; +void Compiler::PostLower(const std::vector& tensor_ids, + const OpDesc* op_desc) { + // Set pipline + // Due to the limitation of popart, if an op has multiple outputs, + // pipline settings needs to be set at the same time auto tensor_ids_set = std::set(tensor_ids.begin(), tensor_ids.end()); - if (op_desc->HasAttr(sIpuIndexAttr)) { auto ipu_index = BOOST_GET_CONST(int, op_desc->GetAttr(sIpuIndexAttr)); builder_->virtualGraph(tensor_ids_set, ipu_index); @@ -639,18 +633,24 @@ void Compiler::SetIpuIndexStage(const std::vector& tensor_ids, if (op_desc->HasAttr(sIpuStageAttr)) { auto ipu_stage = BOOST_GET_CONST(int, op_desc->GetAttr(sIpuStageAttr)); builder_->pipelineStage(tensor_ids_set, ipu_stage); - VLOG(10) << "set " << sIpuStageAttr << "= " << ipu_stage + VLOG(10) << "set " << sIpuStageAttr << " = " << ipu_stage << " for op: " << op_desc->Type(); } } - VLOG(10) << "leave Compiler::SetIpuIndexStage"; + + for (auto& tensor_id : tensor_ids) { + PostLower(tensor_id, op_desc, true); + } } -void Compiler::SetIpuIndexStage(const std::string& tensor_id, - const OpDesc* op_desc) { - VLOG(10) << "enter Compiler::SetIpuIndexStage"; +void Compiler::PostLower(const std::string& tensor_id, const OpDesc* op_desc) { + PostLower(tensor_id, op_desc, false); +} - if (op_desc->HasAttr(sIpuIndexAttr)) { +void Compiler::PostLower(const std::string& tensor_id, const OpDesc* op_desc, + bool skip_pipline) { + // Set pipline + if (!skip_pipline && op_desc->HasAttr(sIpuIndexAttr)) { auto ipu_index = BOOST_GET_CONST(int, op_desc->GetAttr(sIpuIndexAttr)); builder_->virtualGraph(tensor_id, ipu_index); VLOG(10) << "set " << sIpuIndexAttr << " = " << ipu_index @@ -658,32 +658,18 @@ void Compiler::SetIpuIndexStage(const std::string& tensor_id, if (op_desc->HasAttr(sIpuStageAttr)) { auto ipu_stage = BOOST_GET_CONST(int, op_desc->GetAttr(sIpuStageAttr)); builder_->pipelineStage(tensor_id, ipu_stage); - VLOG(10) << "set " << sIpuStageAttr << "= " << ipu_stage + VLOG(10) << "set " << sIpuStageAttr << " = " << ipu_stage << " for op: " << op_desc->Type(); } } - VLOG(10) << "leave Compiler::SetIpuIndexStage"; -} - -void Compiler::SetAMPAttributes(const std::vector& tensor_ids, - const OpDesc* op_desc) { - if (op_desc->Type() == "popart_matmul") { - for (const auto& tensor_id : tensor_ids) { - SetAMPAttributes(tensor_id, op_desc); - } - } -} - -void Compiler::SetAMPAttributes(const std::string& tensor_id, - const OpDesc* op_desc) { - VLOG(10) << "enter Compiler::SetAMPAttributes"; + // Set amp if (op_desc->Type() == "popart_matmul") { if (set_amp_for_all_) { auto amp = ipu_strategy_->available_memory_proportion; if (amp < 0.0f || amp > 1.0) { PADDLE_THROW(platform::errors::InvalidArgument( - "AvailableMemoryProportion %f is invalid, which should be set 0 <= " - "amp <= 1", + "AvailableMemoryProportion %f is invalid, which should be in " + "range [0.0, 1.0]", amp)); } if (amp > 0.0f) { @@ -694,8 +680,8 @@ void Compiler::SetAMPAttributes(const std::string& tensor_id, auto amp = BOOST_GET_CONST(float, op_desc->GetAttr(sAvailMemAttribute)); if (amp < 0.0f || amp > 1.0) { PADDLE_THROW(platform::errors::InvalidArgument( - "AvailableMemoryProportion %f is invalid, which should be set 0 " - "<= amp <= 1", + "AvailableMemoryProportion %f is invalid, which should be in " + "range [0.0, 1.0]", amp)); } if (amp > 0.0f) { @@ -705,17 +691,7 @@ void Compiler::SetAMPAttributes(const std::string& tensor_id, } } } - } - VLOG(10) << "leave Compiler::SetAMPAttributes"; -} - -void Compiler::SetSerializeAttributes( - const std::vector& tensor_ids, const OpDesc* op_desc) { - VLOG(10) << "enter Compiler::SetSerializeAttributes"; - auto tensor_ids_set = - std::set(tensor_ids.begin(), tensor_ids.end()); - - if (op_desc->Type() == "popart_matmul") { + // Set serialize matmul if (op_desc->HasAttr(sMatmulSerializeFactor)) { auto factor = BOOST_GET_CONST(int, op_desc->GetAttr(sMatmulSerializeFactor)); @@ -724,16 +700,9 @@ void Compiler::SetSerializeAttributes( mode = BOOST_GET_CONST(std::string, op_desc->GetAttr(sMatmulSerializeMode)); } - builder_->setSerializeMatMul(tensor_ids_set, mode, (int64_t)factor, true); + builder_->setSerializeMatMul({tensor_id}, mode, factor, true); } } - VLOG(10) << "leave Compiler::SetSerializeAttributes"; -} - -void Compiler::SetSerializeAttributes(const std::string& tensor_id, - const OpDesc* op_desc) { - std::vector tensor_ids = {tensor_id}; - SetSerializeAttributes(tensor_ids, op_desc); } void Compiler::SetCustomOps( @@ -793,29 +762,6 @@ popart::DebugContext Compiler::BuildDebugContext(const OpDesc* op) { return popart::DebugContext(op_identify_id); } -void Compiler::PushNameScope(const OpDesc* op) { - auto op_namescope = BOOST_GET_CONST(std::string, op->GetAttr(sOpNamescope)); - if (op_namescope == "/") { - return; - } - if (!op_namescope.empty()) { - op_namescope.pop_back(); - } - if (!op_namescope.empty()) { - op_namescope.erase(op_namescope.begin()); - } - VLOG(10) << "name_scope is: " << op_namescope; - builder_->pushNameScope(op_namescope); -} - -void Compiler::PopNameScope(const OpDesc* op) { - auto op_namescope = BOOST_GET_CONST(std::string, op->GetAttr(sOpNamescope)); - if (op_namescope == "/") { - return; - } - builder_->popNameScope(); -} - } // namespace ipu } // namespace platform } // namespace paddle diff --git a/paddle/fluid/platform/device/ipu/ipu_compiler.h b/paddle/fluid/platform/device/ipu/ipu_compiler.h index 2d00970bf129750af34dcc9e2239409cd12d897e..bf00a453881b73dcac01851945f12c47764736f4 100644 --- a/paddle/fluid/platform/device/ipu/ipu_compiler.h +++ b/paddle/fluid/platform/device/ipu/ipu_compiler.h @@ -70,7 +70,7 @@ struct CompilerResources { std::unique_ptr optimizer; }; -// helper for lowering graph +// Helper for lowering graph struct GraphHelper { explicit GraphHelper(const Graph *); @@ -81,6 +81,30 @@ struct GraphHelper { std::vector sorted_vars_id; }; +// Helper for adding namescope info +struct NameScopeHelper { + NameScopeHelper(const OpDesc *op, popart::Builder *builder) + : builder_(builder) { + auto op_namescope = BOOST_GET_CONST(std::string, op->GetAttr(sOpNamescope)); + if (op_namescope.empty() || op_namescope == "/") { + return; + } + op_namescope.pop_back(); + op_namescope.erase(op_namescope.begin()); + builder->pushNameScope(op_namescope); + pushed_ = true; + } + + ~NameScopeHelper() { + if (pushed_) { + builder_->popNameScope(); + } + } + + bool pushed_ = false; + popart::Builder *builder_; +}; + class Compiler { public: Compiler(); @@ -119,18 +143,9 @@ class Compiler { const std::vector &tensor_ids); void InsertTensors(const std::vector &output_names, const std::string &tensor_id); - void SetIpuIndexStage(const std::vector &tensor_ids, - const OpDesc *op_desc); - void SetIpuIndexStage(const std::string &tensor_id, const OpDesc *op_desc); - void SetAMPAttributes(const std::vector &tensor_ids, - const OpDesc *op_desc); - void SetAMPAttributes(const std::string &tensor_id, const OpDesc *op_desc); - void SetSerializeAttributes(const std::vector &tensor_ids, - const OpDesc *op_desc); - void SetSerializeAttributes(const std::string &tensor_id, - const OpDesc *op_desc); - void PushNameScope(const OpDesc *op); - void PopNameScope(const OpDesc *op); + void PostLower(const std::vector &, const OpDesc *); + void PostLower(const std::string &, const OpDesc *); + void PostLower(const std::string &, const OpDesc *, bool); private: std::unique_ptr builder_; diff --git a/paddle/fluid/platform/device/ipu/ipu_executor.cc b/paddle/fluid/platform/device/ipu/ipu_executor.cc index 649b291244110e69c364dc50d7840d47040e9ab0..4b8c8286e22e9c1f523545245d7c87b52ec2b59e 100644 --- a/paddle/fluid/platform/device/ipu/ipu_executor.cc +++ b/paddle/fluid/platform/device/ipu/ipu_executor.cc @@ -20,6 +20,40 @@ namespace paddle { namespace platform { namespace ipu { +// Get paddle prefix and popart postfix of weight states +// Format: {popart_postfix, paddle_prefix} +std::vector> GetOptPrePostfix( + const std::string &opt_type) { + std::vector> pre_post_fix; + // Weight self + pre_post_fix.push_back(std::make_pair("", "")); + + // Weight states + // TODO(alleng) support pair("Accl1___", "_moment1_{id!=0}") + if (opt_type == "adam" || opt_type == "lamb" || opt_type == "adamw") { + pre_post_fix.push_back(std::make_pair("Accl1___", "_moment1_0")); + pre_post_fix.push_back(std::make_pair("Accl2___", "_moment2_0")); + pre_post_fix.push_back(std::make_pair("Step___", "_beta1_pow_acc_0")); + } else if (opt_type == "momentum") { + pre_post_fix.push_back(std::make_pair("Accl___", "_velocity_0")); + } else if (opt_type == "adamax") { + pre_post_fix.push_back(std::make_pair("Accl1___", "_moment_0")); + pre_post_fix.push_back(std::make_pair("Accl2___", "_inf_norm__0")); + pre_post_fix.push_back(std::make_pair("Step___", "_beta1_pow_acc_0")); + } else if (opt_type == "adagrad") { + pre_post_fix.push_back(std::make_pair("Accl1___", "_moment_0")); + } else if (opt_type == "adadelta") { + pre_post_fix.push_back(std::make_pair("Accl1___", "__avg_squared_grad_0")); + pre_post_fix.push_back( + std::make_pair("Accl2___", "__avg_squared_update_0")); + } else if (opt_type == "rmsprop") { + pre_post_fix.push_back(std::make_pair("Accl1___", "_mean_square_0")); + pre_post_fix.push_back(std::make_pair("Accl2___", "_mean_grad_0")); + pre_post_fix.push_back(std::make_pair("Accl3___", "_momentum__0")); + } + return pre_post_fix; +} + Executor::~Executor() { Detach(); session_.reset(); diff --git a/paddle/fluid/platform/device/ipu/ipu_strategy.cc b/paddle/fluid/platform/device/ipu/ipu_strategy.cc index f52499a8d8fda412f2ef47caad421a193371f8be..c208a0eca57076ff28c963c8ee655f75ee0af374 100644 --- a/paddle/fluid/platform/device/ipu/ipu_strategy.cc +++ b/paddle/fluid/platform/device/ipu/ipu_strategy.cc @@ -412,6 +412,15 @@ IpuStrategy::IpuStrategy() { RegisterGetter(map_options_getter, options_type, "gcl_options", "map", [&]() { return popart_options.gclOptions; }); + + // Default options + + // Can also be set as a custom logger in python, like using tqdm + popart_options.compilationProgressLogger = [](int progress, int total) { + if (progress % 10 == 0) { + VLOG(1) << "compile progress: " << progress << "%"; + } + }; } void IpuStrategy::AddBoolOption(const std::string& option, bool value) { @@ -513,6 +522,11 @@ void IpuStrategy::AddCustomOp(const std::string& paddle_op, IpuCustomOpIdentifier(paddle_op, popart_op, domain, version)); } +void IpuStrategy::SetCompilationProgressLogger( + const std::function& logger) { + popart_options.compilationProgressLogger = logger; +} + std::string IpuStrategy::GetOption(const std::string& option) { return get(option, options_getter); } diff --git a/paddle/fluid/platform/device/ipu/ipu_strategy.h b/paddle/fluid/platform/device/ipu/ipu_strategy.h index 1802eb16e58955c57586eecd97c95f163f846d46..26566bc18fed034265e472676772893314768a30 100644 --- a/paddle/fluid/platform/device/ipu/ipu_strategy.h +++ b/paddle/fluid/platform/device/ipu/ipu_strategy.h @@ -125,6 +125,8 @@ class IpuStrategy { const std::vector &values); void AddCustomOp(const std::string &paddle_op, const std::string &popart_op, const std::string &domain, int version); + void SetCompilationProgressLogger( + const std::function &logger); std::string GetOption(const std::string &); std::vector GetVectorOption(const std::string &); diff --git a/paddle/fluid/platform/device/ipu/ipu_utils.cc b/paddle/fluid/platform/device/ipu/ipu_utils.cc index 720de822608b6a78a3518f4717faeae87e9b2865..843f3ffde9e4556b91b34bee8e320fc2d53958c2 100644 --- a/paddle/fluid/platform/device/ipu/ipu_utils.cc +++ b/paddle/fluid/platform/device/ipu/ipu_utils.cc @@ -184,27 +184,6 @@ bool GetBoolEnv(std::string str) { } } -std::vector> GetOptPrePostfix( - const std::string& opt_type) { - // format: {popart_tensor_id, paddle_tensor_id}, ... - std::vector> pre_post_fix; - - if (opt_type == "adam" || opt_type == "lamb") { - pre_post_fix.push_back(std::make_pair("", "")); - pre_post_fix.push_back(std::make_pair("Accl1___", "_moment1_0")); - pre_post_fix.push_back(std::make_pair("Accl2___", "_moment2_0")); - pre_post_fix.push_back(std::make_pair("Step___", "_beta1_pow_acc_0")); - } else if (opt_type == "sgd" || opt_type == "momentum") { - // sgd - pre_post_fix.push_back(std::make_pair("", "")); - } else { - pre_post_fix.push_back(std::make_pair("", "")); - // - } - - return pre_post_fix; -} - int RequestIpus(const int num_ipus) { // num_ipus must be pow(2, n); return std::pow(2, ceil(log2(num_ipus))); diff --git a/paddle/fluid/platform/device/ipu/ipu_utils.h b/paddle/fluid/platform/device/ipu/ipu_utils.h index 7644513cc0207885c3b01709be5b894c532f4647..50859aebdb311e663a4e9c97a159e7377c72c922 100644 --- a/paddle/fluid/platform/device/ipu/ipu_utils.h +++ b/paddle/fluid/platform/device/ipu/ipu_utils.h @@ -229,9 +229,6 @@ struct ConstantOpAttrVisitor : public boost::static_visitor { void operator()(boost::blank) const { RaiseError(); } }; -std::vector> GetOptPrePostfix( - const std::string& opt_type); - int RequestIpus(const int num_ipus); } // namespace ipu diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index dc554a9c5ae1a594cd054d8a5efd4f3094887768..602a0345b04fe98b820ab6ab79fd6568c978cfed 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -4357,7 +4357,10 @@ All parameter, weight, gradient are variables in Paddle. for (auto element : opt) { auto option_name = element.first.cast(); VLOG(10) << "Set option: " << option_name; - if (py::isinstance(element.second)) { + if (option_name == "compilation_progress_logger") { + self.SetCompilationProgressLogger( + element.second.cast()); + } else if (py::isinstance(element.second)) { self.AddBoolOption(option_name, element.second.cast()); } else if (py::isinstance(element.second)) { self.AddDoubleOption(option_name, diff --git a/python/paddle/fluid/tests/unittests/ipu/CMakeLists.txt b/python/paddle/fluid/tests/unittests/ipu/CMakeLists.txt index 79a2430a161703348824d8e4e687bf85569c408a..4826b37512614e526f71adb5d9812f9a94069675 100644 --- a/python/paddle/fluid/tests/unittests/ipu/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/ipu/CMakeLists.txt @@ -11,4 +11,5 @@ if(WITH_IPU) set_tests_properties(test_conv_op_ipu PROPERTIES TIMEOUT 300) set_tests_properties(test_elemetwise_x_op_ipu PROPERTIES TIMEOUT 300) set_tests_properties(test_reduce_x_op_ipu PROPERTIES TIMEOUT 600) + set_tests_properties(test_save_load_ipu PROPERTIES TIMEOUT 600) endif() diff --git a/python/paddle/fluid/tests/unittests/ipu/test_ipu_strategy_ipu.py b/python/paddle/fluid/tests/unittests/ipu/test_ipu_strategy_ipu.py index debd9ed19827cd3cf9137f7a4043550a5065201c..45f75f1b4df81ef883f8faba0e96bbf54d7c761a 100644 --- a/python/paddle/fluid/tests/unittests/ipu/test_ipu_strategy_ipu.py +++ b/python/paddle/fluid/tests/unittests/ipu/test_ipu_strategy_ipu.py @@ -73,10 +73,15 @@ class TestIpuStrategy(unittest.TestCase): 'autoReport.directory': 'path', 'autoReport.all': 'true' } + options['random_seed'] = 1234 for k, v in options.items(): ipu_strategy.set_options({k: v}) assert v == ipu_strategy.get_option(k), f"set {k} to {v} failed " + # The custom logger need 2 int as inputs + logger = lambda progress, total: print(f"compile progrss: {progress}/{total}") + ipu_strategy.set_options({'compilation_progress_logger': logger}) + if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/ipu/test_save_load_ipu.py b/python/paddle/fluid/tests/unittests/ipu/test_save_load_ipu.py index ba6eb4d38bcf22830f3320ab8c29f30e7173805d..c8f0961baa480ccbef09b807a5b300b0338dd62b 100644 --- a/python/paddle/fluid/tests/unittests/ipu/test_save_load_ipu.py +++ b/python/paddle/fluid/tests/unittests/ipu/test_save_load_ipu.py @@ -14,9 +14,11 @@ import tempfile import unittest +from functools import partial import numpy as np import paddle +import paddle.optimizer import paddle.static from paddle.fluid.tests.unittests.ipu.op_test_ipu import IPUOpTest @@ -28,7 +30,8 @@ class TestBase(IPUOpTest): self.set_atol() self.set_data_feed() self.set_feed_attr() - self.set_op_attrs() + self.set_attrs() + self.set_optimizer() def set_data_feed(self): data = np.random.uniform(size=[1, 3, 10, 10]) @@ -39,15 +42,16 @@ class TestBase(IPUOpTest): self.feed_shape = [x.shape for x in self.feed_fp32.values()] self.feed_list = list(self.feed_fp32.keys()) - def set_op_attrs(self): + def set_attrs(self): self.attrs = {} self.attrs['steps'] = 100 self.attrs['save_at_step'] = 20 - self.attrs['is_training'] = True - self.attrs['opt_type'] = 'sgd' self.attrs['enable_fp16'] = False self.attrs['model_path'] = tempfile.TemporaryDirectory() + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.SGD, learning_rate=1e-1) + def _test_base(self, save_otherwise_load): scope = paddle.static.Scope() main_prog = paddle.static.Program() @@ -71,16 +75,8 @@ class TestBase(IPUOpTest): name='conv2d') loss = paddle.mean(conv1) - if self.attrs['is_training']: - if self.attrs['opt_type'] == 'sgd': - sgd = paddle.optimizer.SGD(learning_rate=1e-2) - sgd.minimize(loss) - elif self.attrs['opt_type'] == 'adam': - adam = paddle.optimizer.Adam(learning_rate=1e-2) - adam.minimize(loss) - elif self.attrs['opt_type'] == 'lamb': - lamb = paddle.optimizer.Lamb(learning_rate=1e-2) - lamb.minimize(loss) + # apply optimizer + self.optimizer().minimize(loss) fetch_list = [loss.name] place = paddle.IPUPlace() @@ -91,8 +87,7 @@ class TestBase(IPUOpTest): paddle.static.load(main_prog, self.attrs['model_path'].name) ipu_strategy = paddle.static.IpuStrategy() - ipu_strategy.set_graph_config( - is_training=self.attrs['is_training']) + ipu_strategy.set_graph_config(is_training=True) ipu_strategy.set_precision_config( enable_fp16=self.attrs['enable_fp16']) ipu_program = paddle.static.IpuCompiledProgram( @@ -131,62 +126,109 @@ class TestBase(IPUOpTest): self.attrs['model_path'].cleanup() +class TestMomentum(TestBase): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Momentum, learning_rate=1e-1) + + class TestAdam(TestBase): - def set_op_attrs(self): - self.attrs = {} - self.attrs['steps'] = 100 - self.attrs['save_at_step'] = 20 - self.attrs['is_training'] = True - self.attrs['opt_type'] = 'adam' - self.attrs['enable_fp16'] = False - self.attrs['model_path'] = tempfile.TemporaryDirectory() + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adam, learning_rate=1e-1) class TestLamb(TestBase): - def set_op_attrs(self): - self.attrs = {} - self.attrs['steps'] = 100 - self.attrs['save_at_step'] = 20 - self.attrs['is_training'] = True - self.attrs['opt_type'] = 'lamb' - self.attrs['enable_fp16'] = False - self.attrs['model_path'] = tempfile.TemporaryDirectory() + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Lamb, learning_rate=1e-1) + + +class TestAdamW(TestBase): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.AdamW, learning_rate=1e-1) + + +class TestAdamax(TestBase): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adamax, learning_rate=1e-1) + + +class TestAdagrad(TestBase): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adagrad, learning_rate=1e-1) + + +class TestAdadelta(TestBase): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adagrad, learning_rate=1e-1) + + +class TestRMSProp(TestBase): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.RMSProp, learning_rate=1e-1) + + +class TestCenteredRMSProp(TestBase): + def set_optimizer(self): + self.optimizer = partial( + paddle.optimizer.RMSProp, learning_rate=1e-1, centered=True) @unittest.skipIf(IPUOpTest.use_ipumodel(), "skip for ipumodel") class TestSGDFP16(TestBase): - def set_op_attrs(self): + def set_attrs(self): self.attrs = {} self.attrs['steps'] = 100 self.attrs['save_at_step'] = 20 - self.attrs['is_training'] = True - self.attrs['opt_type'] = 'sgd' self.attrs['enable_fp16'] = True self.attrs['model_path'] = tempfile.TemporaryDirectory() + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.SGD, learning_rate=1e-1) -@unittest.skipIf(IPUOpTest.use_ipumodel(), "skip for ipumodel") -class TestAdamFP16(TestBase): - def set_op_attrs(self): - self.attrs = {} - self.attrs['steps'] = 100 - self.attrs['save_at_step'] = 20 - self.attrs['is_training'] = True - self.attrs['opt_type'] = 'adam' - self.attrs['enable_fp16'] = True - self.attrs['model_path'] = tempfile.TemporaryDirectory() +class TestMomentumFp16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Momentum, learning_rate=1e-1) -@unittest.skipIf(IPUOpTest.use_ipumodel(), "skip for ipumodel") -class TestLambFP16(TestBase): - def set_op_attrs(self): - self.attrs = {} - self.attrs['steps'] = 100 - self.attrs['save_at_step'] = 20 - self.attrs['is_training'] = True - self.attrs['opt_type'] = 'lamb' - self.attrs['enable_fp16'] = True - self.attrs['model_path'] = tempfile.TemporaryDirectory() + +class TestAdamFP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adam, learning_rate=1e-1) + + +class TestLambFP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Lamb, learning_rate=1e-1) + + +class TestAdamWFP16FP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.AdamW, learning_rate=1e-1) + + +class TestAdamaxFP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adamax, learning_rate=1e-1) + + +class TestAdagradFP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adagrad, learning_rate=1e-1) + + +class TestAdadeltaFP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.Adagrad, learning_rate=1e-1) + + +class TestRMSPropFP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial(paddle.optimizer.RMSProp, learning_rate=1e-1) + + +class TestCenteredRMSPropFP16(TestSGDFP16): + def set_optimizer(self): + self.optimizer = partial( + paddle.optimizer.RMSProp, learning_rate=1e-1, centered=True) if __name__ == "__main__": diff --git a/tools/dockerfile/Dockerfile.ipu b/tools/dockerfile/Dockerfile.ipu index 715bd34b908bebacb24d13543322e1d9b27b357d..08536ae401fe174f3630c259dce68b4fd038d8d3 100644 --- a/tools/dockerfile/Dockerfile.ipu +++ b/tools/dockerfile/Dockerfile.ipu @@ -1,10 +1,10 @@ # A image for building paddle binaries # build docker image -# docker build -t paddlepaddle/paddle:ipu-dev-2.3.0 -f tools/dockerfile/Dockerfile.ipu . +# docker build -t paddlepaddle/paddle:latest-dev-ipu -f tools/dockerfile/Dockerfile.ipu . # run a container -# docker run --ulimit memlock=-1:-1 --net=host --cap-add=IPC_LOCK --device=/dev/infiniband/ --ipc=host --rm -it paddlepaddle/paddle:ipu-dev-2.3.0 bash +# docker run --ulimit memlock=-1:-1 --net=host --cap-add=IPC_LOCK --device=/dev/infiniband/ --ipc=host --rm -it paddlepaddle/paddle:latest-dev-ipu bash FROM graphcore/poplar:2.3.0 MAINTAINER PaddlePaddle Authors