def _initialize_graph_builder(self, training):
"""Creates a new OrtModuleGraphBuilder, initializes it and saves it to self._graph_builder"""
# All initializer names along with user inputs are a part of the onnx graph inputs
# since the onnx model was exported with the flag keep_initializers_as_inputs=True
onnx_initializer_names = {p.name for p in self._onnx_model.graph.input}
# TODO: PyTorch exporter bug: changes the initializer order in ONNX model
initializer_names = [
name for name, _ in self._flattened_module.named_parameters()
if name in onnx_initializer_names
]
initializer_names_to_train = [
name for name, param in self._flattened_module.named_parameters()
if param.requires_grad and name in onnx_initializer_names
]
# Build and optimize the full graph
grad_builder_config = C.OrtModuleGraphBuilderConfiguration()
grad_builder_config.initializer_names = initializer_names
grad_builder_config.initializer_names_to_train = initializer_names_to_train
grad_builder_config.input_names_require_grad = self._input_info.require_grad_names
grad_builder_config.build_gradient_graph = training
grad_builder_config.graph_transformer_config = self._get_graph_transformer_config(
)
grad_builder_config.loglevel = _logger.ortmodule_loglevel_to_onnxruntime_c_loglevel(
self._loglevel)
self._graph_builder = C.OrtModuleGraphBuilder()
# It is assumed here that the order and names of the inputs and outputs are not modified by the backend in any way
# and are kept as they appear in the exported onnx model.
self._graph_builder.initialize(self._onnx_model.SerializeToString(),
grad_builder_config)
def _initialize_graph_builder(self, training):
"""Creates a new OrtModuleGraphBuilder, initializes it and saves it to self._graph_builder"""
# TODO: PyTorch exporter bug: changes the initializer order in ONNX model
initializer_names = [name for name, _ in self._flattened_module.named_parameters()]
initializer_names_to_train = [name for name,
param in self._flattened_module.named_parameters() if param.requires_grad]
# Build and optimize the full graph
grad_builder_config = C.OrtModuleGraphBuilderConfiguration()
grad_builder_config.initializer_names = initializer_names
grad_builder_config.initializer_names_to_train = initializer_names_to_train
grad_builder_config.input_names_require_grad = self._input_info.require_grad_names
grad_builder_config.build_gradient_graph = training
grad_builder_config.graph_transformer_config = C.GraphTransformerConfiguration()
grad_builder_config.graph_transformer_config.propagate_cast_ops_level = self._propagate_cast_ops_level
grad_builder_config.graph_transformer_config.propagate_cast_ops_allow = self._propagate_cast_ops_allow
grad_builder_config.graph_transformer_config.allow_layer_norm_mod_precision = self._allow_layer_norm_mod_precision
grad_builder_config.loglevel = {_logger.LogLevel.VERBOSE : C.Severity.VERBOSE,
_logger.LogLevel.INFO : C.Severity.INFO,
_logger.LogLevel.WARNING : C.Severity.WARNING,
_logger.LogLevel.ERROR : C.Severity.ERROR,
_logger.LogLevel.FATAL : C.Severity.FATAL}.get(self._loglevel, C.Severity.WARNING)
self._graph_builder = C.OrtModuleGraphBuilder()
self._graph_builder.initialize(self._onnx_model.SerializeToString(), grad_builder_config)
def _initialize_graph_builder(self, training):
"""Creates a new OrtModuleGraphBuilder, initializes it and saves it to self._graph_builder"""
# TODO: PyTorch exporter bug: changes the initializer order in ONNX model
initializer_names = [
name for name, _ in self._flattened_module.named_parameters()
]
initializer_names_to_train = [
name for name, param in self._flattened_module.named_parameters()
if param.requires_grad
]
# Build and optimize the full graph
grad_builder_config = C.OrtModuleGraphBuilderConfiguration()
grad_builder_config.initializer_names = initializer_names
grad_builder_config.initializer_names_to_train = initializer_names_to_train
grad_builder_config.input_names_require_grad = self._input_info.require_grad_names
grad_builder_config.build_gradient_graph = training
grad_builder_config.graph_transformer_config = C.GraphTransformerConfiguration(
)
grad_builder_config.graph_transformer_config.propagate_cast_ops_level = self._propagate_cast_ops_level
grad_builder_config.graph_transformer_config.propagate_cast_ops_allow = self._propagate_cast_ops_allow
self._graph_builder = C.OrtModuleGraphBuilder()
self._graph_builder.initialize(self._onnx_model.SerializeToString(),
grad_builder_config)
def _initialize_graph_builder(self, training):
"""Creates a new OrtModuleGraphBuilder, initializes it and saves it to self._graph_builder"""
# All initializer names along with user inputs are a part of the onnx graph inputs
# since the onnx model was exported with the flag keep_initializers_as_inputs=True
onnx_initializer_names = {
p.name
for p in self._onnx_models.exported_model.graph.input
}
# TODO: PyTorch exporter bug: changes the initializer order in ONNX model
initializer_names = [
name for name, _ in self._flattened_module.named_parameters()
if name in onnx_initializer_names
]
initializer_names_to_train = [
name for name, param in self._flattened_module.named_parameters()
if param.requires_grad and name in onnx_initializer_names
]
# Build and optimize the full graph
grad_builder_config = C.OrtModuleGraphBuilderConfiguration()
grad_builder_config.initializer_names = initializer_names
grad_builder_config.initializer_names_to_train = initializer_names_to_train
grad_builder_config.input_names_require_grad = self._input_info.require_grad_names
grad_builder_config.build_gradient_graph = training
grad_builder_config.graph_transformer_config = self._get_graph_transformer_config(
)
grad_builder_config.enable_caching = self._enable_grad_acc_optimization
grad_builder_config.loglevel = _logger.ortmodule_loglevel_to_onnxruntime_c_loglevel(
self._debug_options.logging.log_level)
grad_builder_config.use_memory_efficient_gradient = self._use_memory_efficient_gradient
self._graph_builder = C.OrtModuleGraphBuilder()
# It is assumed here that the order and names of the inputs and outputs are not modified by the backend in any way
# and are kept as they appear in the exported onnx model.
self._graph_builder.initialize(
self._onnx_models.exported_model.SerializeToString(),
grad_builder_config)
# TODO: Explore ways to make self._graph_info.initializer_names and self._graph_info.initializer_names_to_train
# a set (unordered_set in the backend) that does not require a copy on each reference.
self._graph_initializer_names = set(initializer_names)
self._graph_initializer_names_to_train = set(
initializer_names_to_train)
# Initializers can be cached and used since they are expected not to be re-instantiated
# between forward calls.
self._graph_initializers = [
param for name, param in self._flattened_module.named_parameters()
if name in self._graph_initializer_names
]