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forward backward contiguous ones #57189

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Sep 12, 2023
Merged

forward backward contiguous ones #57189

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77 changes: 75 additions & 2 deletions paddle/fluid/eager/auto_code_generator/generator/eager_gen.py
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Original file line number Diff line number Diff line change
Expand Up @@ -81,6 +81,30 @@
"matmul_grad": {"x": "grad_y", "y": "grad_x"},
}

strided_op_list = {
"as_complex",
"as_real",
"as_strided",
"real",
"imag",
"diagonal",
"flatten",
"flatten_infer",
"reshape",
"slice",
"squeeze_infer",
"squeeze",
"strided_slice",
"strided_slice_raw",
"tensor_unfold",
"transpose",
"unbind",
"unsqueeze_infer",
"unsqueeze",
"view_shape",
"view_dtype",
}


#########
# Utils #
Expand Down Expand Up @@ -234,6 +258,9 @@ class {} : public egr::GradNodeBase {{
// Node Declaration
std::shared_ptr<{}> grad_node;

// Pre contiguous tensor in not strided op, if 1)require_any_grad=true; 2) need wrapper to backward; 3) not contiguous
{}

// Set grad_node before API Call
{}

Expand Down Expand Up @@ -409,6 +436,7 @@ class {} : public egr::GradNodeBase {{
#include "paddle/fluid/eager/nan_inf_utils.h"
#include "paddle/fluid/eager/api/manual/eager_manual/dygraph_forward_api.h"
#include "paddle/phi/core/flags.h"
#include "paddle/phi/api/lib/data_transform.h"

PHI_DECLARE_bool(check_nan_inf);
PHI_DECLARE_string(tensor_operants_mode);
Expand Down Expand Up @@ -984,6 +1012,7 @@ def GenerateNodeCreationCodes(self, for_backward=False, is_inplaced=False):
set_attributes_list.append(set_attributes)
set_attributes_str = "\n".join(set_attributes_list)

need_pre_contiguous_set = set()
# SetTensorWrappers
set_input_tensor_wrappers_list = []
set_output_tensor_wrappers_list = []
Expand All @@ -1007,12 +1036,30 @@ def GenerateNodeCreationCodes(self, for_backward=False, is_inplaced=False):
{"indent": indent, "name": name}
)
else:
set_tensor_wrappers = f"{indent}if({name}) grad_node->SetTensorWrapper{name}(*{name});"
if (
(forward_api_name in strided_op_list)
or for_backward
or IsVectorTensorType(atype)
or (name in self.optional_inputs)
):
set_tensor_wrappers = f"{indent}if({name}) grad_node->SetTensorWrapper{name}(*{name});"
else:
need_pre_contiguous_set.add(name)
set_tensor_wrappers = f"{indent}if({name}) grad_node->SetTensorWrapper{name}(*{name}_tmp);"
else:
if is_inplace_input:
set_tensor_wrappers = f"{indent}auto {name}_clone = paddle::experimental::assign({name});\n{indent}grad_node->SetTensorWrapper{name}({name}_clone);"
else:
set_tensor_wrappers = f"{indent}grad_node->SetTensorWrapper{name}({name});"
if (
(forward_api_name in strided_op_list)
or for_backward
or IsVectorTensorType(atype)
or (name in self.optional_inputs)
):
set_tensor_wrappers = f"{indent}grad_node->SetTensorWrapper{name}({name});"
else:
need_pre_contiguous_set.add(name)
set_tensor_wrappers = f"{indent}grad_node->SetTensorWrapper{name}({name}_tmp);"
set_input_tensor_wrappers_list.append(set_tensor_wrappers)
else: # Forwad's output as backward's input
if num_fwd_outputs > 1:
Expand All @@ -1032,6 +1079,24 @@ def GenerateNodeCreationCodes(self, for_backward=False, is_inplaced=False):
set_output_tensor_wrappers_list
)

if (forward_api_name in strided_op_list) or for_backward:
self.inputs_call_list_tmp = None
self.node_creation_pre_contiguous_str = ""
else:
self.inputs_call_list_tmp = self.inputs_call_list
pre_contiguous_list = []
for name, (ttype, pos) in forward_inputs_position_map.items():
if name in need_pre_contiguous_set:
pre_contiguous_list.append(
f"{indent}const auto& {name}_tmp = (require_any_grad && {name}.is_dense_tensor() && !std::dynamic_pointer_cast<phi::DenseTensor>({name}.impl())->meta().is_contiguous()) ? paddle::Tensor(std::make_shared<phi::DenseTensor>(std::move(paddle::experimental::Trans2Contiguous(*(std::dynamic_pointer_cast<phi::DenseTensor>({name}.impl())))))) : {name};"
)
self.inputs_call_list_tmp[pos] = (
self.inputs_call_list_tmp[pos] + '_tmp'
)
self.node_creation_pre_contiguous_str = "\n".join(
pre_contiguous_list
)

# SetGradOutMeta & SetEdges
grad_node_out_list = []
set_grad_out_meta_list = []
Expand Down Expand Up @@ -1470,6 +1535,7 @@ def GenerateForwardDefinitionAndDeclaration(self, is_inplaced):
inputs_args_declaration_str = ", ".join(inputs_args_declaration_list)
inputs_args_definition_str = ", ".join(inputs_args_definition_list)
inputs_call_args_str = ", ".join(inputs_call_list)
self.inputs_call_list = inputs_call_list

# Forward Full Logic
function_name = forward_api_name
Expand Down Expand Up @@ -1656,6 +1722,12 @@ def GenerateForwardDefinitionAndDeclaration(self, is_inplaced):
node_creation_str = self.node_creation_str
node_creation_before_call_str = self.node_creation_before_call_str
node_creation_after_call_str = self.node_creation_after_call_str
node_creation_pre_contiguous_str = (
self.node_creation_pre_contiguous_str
)
if self.inputs_call_list_tmp is not None:
inputs_call_args_str_tmp = ", ".join(self.inputs_call_list_tmp)
forward_call_str = f"{indent}{api_out_type} api_result = paddle::experimental::{namespace}{function_name}({inputs_call_args_str_tmp});"

dygraph_event_str = f"{indent}paddle::platform::RecordEvent dygraph_entrance_record_event(\"{forward_api_name} dygraph\", paddle::platform::TracerEventType::Operator, 1);\n"
forward_ad_function_name = GetDygraphForwardFunctionName(
Expand Down Expand Up @@ -1767,6 +1839,7 @@ def GenerateForwardDefinitionAndDeclaration(self, is_inplaced):
before_log_str,
compute_require_grad_args_str,
self.grad_node_name,
node_creation_pre_contiguous_str,
node_creation_before_call_str,
forward_call_str,
check_nan_inf_str,
Expand Down