diff --git a/paddle/fluid/eager/auto_code_generator/eager_generator.cc b/paddle/fluid/eager/auto_code_generator/eager_generator.cc
index b3657a9894f82b..fe29792b6e75c4 100644
--- a/paddle/fluid/eager/auto_code_generator/eager_generator.cc
+++ b/paddle/fluid/eager/auto_code_generator/eager_generator.cc
@@ -33,14 +33,18 @@ static std::unordered_map<std::string, paddle::framework::AttributeMap>
operators_with_attrs = {};
static std::unordered_set<std::string> operators_to_skip = {
- "chunk_eval", // Stupid tensor name
- "minus", "pull_sparse", "pull_box_extended_sparse",
- "pull_sparse_v2", "pull_box_sparse", "fused_attention",
- "diag_v2", "c_split"};
+ "minus",
+};
static std::unordered_set<std::string> operators_to_codegen = {};
static std::unordered_set<std::string> skipped_operators = {};
+static std::string LegalizeVariableName(const std::string& var_name) {
+ std::string ret = var_name;
+ std::replace(ret.begin(), ret.end(), '-', '_'); // replace all '-' to '_'
+ return ret;
+}
+
static std::string AttrTypeToString(const proto::AttrType& type) {
std::string ret;
switch (type) {
@@ -608,6 +612,9 @@ static bool CollectGradInformationFromOpInfo(
}
VLOG(6) << "Prepared Default Attributes Map, size = " << default_attrs.size();
+ for (const auto& iter : default_attrs) {
+ VLOG(6) << iter.first;
+ }
/* ---------------------------- */
/* --------- Backward --------- */
@@ -1052,24 +1059,25 @@ static std::pair<std::string, std::string> GenerateForwardFunctionContents(
const std::string& output_name = output.name();
std::string out_tensor_str;
size_t return_position = fwd_outputs_name_pos_map.at(output_name);
+ std::string output_varname = LegalizeVariableName(output_name);
if (output.duplicable()) {
const char* FWD_OUT_TENSORS_TEMPLATE =
" std::vector<egr::EagerTensor> %s = "
"egr::EagerUtils::GetOutputs(outs[\"%s\"]);\n";
out_tensor_str = paddle::string::Sprintf(FWD_OUT_TENSORS_TEMPLATE,
- output_name, output_name);
+ output_varname, output_name);
return_types[return_position] = "std::vector<egr::EagerTensor>";
} else {
const char* FWD_OUT_TENSOR_TEMPLATE =
" egr::EagerTensor %s = "
"egr::EagerUtils::GetOutput(outs[\"%s\"][0]);\n";
out_tensor_str = paddle::string::Sprintf(FWD_OUT_TENSOR_TEMPLATE,
- output_name, output_name);
+ output_varname, output_name);
return_types[return_position] = "egr::EagerTensor";
}
- return_contents[return_position] = output_name;
+ return_contents[return_position] = output_varname;
generated_function_body += out_tensor_str;
}
generated_function_body += "\n";
@@ -1280,23 +1288,76 @@ static std::string GenerateGradNodeCCContents(
if (grad_outs_slotname_map.count(grad_output_name)) {
// Fwd Tensor
- const std::string& fwd_input_name =
- grad_outs_slotname_map.at(grad_output_name);
- size_t fwd_input_position = fwd_inputs_name_pos_map.at(fwd_input_name);
-
- if (duplicable_input_name_set.count(fwd_input_name)) {
- const char* GRAD_OUTS_CONTENT_TEMPLATE =
- "{ \"%s\", egr::EagerUtils::ConstructDuplicableOutput( "
- "this->OutputMeta()[%d].Size() ) },";
+ const std::string& fwd_name = grad_outs_slotname_map.at(grad_output_name);
+
+ /* Handle Special Case: "PullSparseOp", etc
+
+ Forward:
+
+ Ids W
+ | |
+ PullSparseOp
+ |
+ Out
+
+ Backward:
+
+ Ids GradOut W
+ | | |
+ PullSparseGradOp
+ |
+ GradOut
+
+ Its grad output "GradOut" corresponds to forward output "Out",
+ where there is a hiden inplace involved. So we find "GradOut"'s index
+ in
+ grads, and perform the inplace operation by constructing outs =
+ {{"Out", grads[i]}}
+
+ GradOut -> Out -> fwd_output_pos -> grads position -> grads[i]
+ outs = {{"Out", grads[i]}}
+
+ For returns, append "GradOut" to the very end of return list.
+ */
+ if (!fwd_inputs_name_pos_map.count(fwd_name)) {
+ PADDLE_ENFORCE(fwd_outputs_name_pos_map.count(fwd_name),
+ paddle::platform::errors::Fatal(
+ "fwd_name not found in fwd_inputs_name_pos_map nor "
+ "fwd_outputs_name_pos_map"));
+
+ size_t grads_position = fwd_outputs_name_pos_map.at(fwd_name);
+ std::string grad_ptr_name = fwd_name + "_ptrs";
+ const char* GET_GRADS_PTR_TEMPLATE =
+ " std::vector<std::shared_ptr<egr::EagerTensor>> %s;\n"
+ " for(const auto& t : grads[%d]) {\n "
+ "%s.emplace_back(std::move(std::make_shared<egr::EagerTensor>(t)));"
+ "\n }\n";
+ std::string grads_ptr_str =
+ paddle::string::Sprintf(GET_GRADS_PTR_TEMPLATE, grad_ptr_name,
+ grads_position, grad_ptr_name);
+ generated_grad_function_body += grads_ptr_str;
+ generated_grad_function_body += "\n";
+
+ const char* GRAD_OUTS_CONTENT_TEMPLATE = "{ \"%s\", %s },";
outs_contents_str += paddle::string::Sprintf(
- GRAD_OUTS_CONTENT_TEMPLATE, grad_output_name, fwd_input_position);
+ GRAD_OUTS_CONTENT_TEMPLATE, grad_output_name, grad_ptr_name);
+
} else {
- const char* GRAD_OUTS_CONTENT_TEMPLATE =
- "{ \"%s\", "
- "{std::make_shared<egr::EagerTensor>(egr::Controller::Instance()."
- "GenerateUniqueName())}},";
- outs_contents_str += paddle::string::Sprintf(GRAD_OUTS_CONTENT_TEMPLATE,
- grad_output_name);
+ size_t fwd_input_position = fwd_inputs_name_pos_map.at(fwd_name);
+ if (duplicable_input_name_set.count(fwd_name)) {
+ const char* GRAD_OUTS_CONTENT_TEMPLATE =
+ "{ \"%s\", egr::EagerUtils::ConstructDuplicableOutput( "
+ "this->OutputMeta()[%d].Size() ) },";
+ outs_contents_str += paddle::string::Sprintf(
+ GRAD_OUTS_CONTENT_TEMPLATE, grad_output_name, fwd_input_position);
+ } else {
+ const char* GRAD_OUTS_CONTENT_TEMPLATE =
+ "{ \"%s\", "
+ "{std::make_shared<egr::EagerTensor>(egr::Controller::Instance()."
+ "GenerateUniqueName())}},";
+ outs_contents_str += paddle::string::Sprintf(
+ GRAD_OUTS_CONTENT_TEMPLATE, grad_output_name);
+ }
}
} else {
PADDLE_THROW(platform::errors::Fatal(
@@ -1340,15 +1401,39 @@ static std::string GenerateGradNodeCCContents(
// [Generation] Get Return
std::string outputs_str = "";
+ size_t num_appended_outputs = 0;
for (auto iter : grad_outs) {
const std::string& grad_out_name = iter.first;
- size_t fwd_input_position =
- fwd_inputs_name_pos_map.at(grad_outs_slotname_map.at(grad_out_name));
+ const std::string& fwd_name = grad_outs_slotname_map.at(grad_out_name);
+
+ if (fwd_inputs_name_pos_map.count(fwd_name)) {
+ size_t fwd_input_position = fwd_inputs_name_pos_map.at(fwd_name);
+ const char* BWD_OUTPUT_TEMPLATE =
+ " outputs[%d] = egr::EagerUtils::GetOutputs(outs[\"%s\"]);\n";
+ outputs_str += paddle::string::Sprintf(BWD_OUTPUT_TEMPLATE,
+ fwd_input_position, grad_out_name);
+ num_appended_outputs++;
+ } else {
+ PADDLE_ENFORCE(fwd_outputs_name_pos_map.count(fwd_name),
+ paddle::platform::errors::Fatal(
+ "fwd_name not found in fwd_inputs_name_pos_map nor "
+ "fwd_outputs_name_pos_map"));
+ }
+ }
- const char* BWD_OUTPUT_TEMPLATE =
- " outputs[%d] = egr::EagerUtils::GetOutputs(outs[\"%s\"]);\n";
- outputs_str += paddle::string::Sprintf(BWD_OUTPUT_TEMPLATE,
- fwd_input_position, grad_out_name);
+ /* Handle Special Case: "PullSparseOp", etc
+ For returns, append "GradOut" to the very end of return list. */
+ for (auto iter : grad_outs) {
+ const std::string& grad_out_name = iter.first;
+ const std::string& fwd_name = grad_outs_slotname_map.at(grad_out_name);
+
+ if (fwd_outputs_name_pos_map.count(fwd_name)) {
+ const char* BWD_OUTPUT_TEMPLATE =
+ " outputs[%d] = egr::EagerUtils::GetOutputs(outs[\"%s\"]);\n";
+ outputs_str += paddle::string::Sprintf(
+ BWD_OUTPUT_TEMPLATE, num_appended_outputs, grad_out_name);
+ num_appended_outputs++;
+ }
}
const char* BWD_RETURN_TEMPLATE =
@@ -1722,6 +1807,10 @@ static void PrepareAttrMapForOps() {
operators_with_attrs["transfer_dtype"] = {};
operators_with_attrs["transfer_dtype"]["out_dtype"] = 5;
operators_with_attrs["transfer_dtype"]["in_dtype"] = 5;
+
+ // Handle "c_split"
+ operators_with_attrs["c_split"] = {};
+ operators_with_attrs["c_split"]["nranks"] = 1;
}
static void CollectOperatorsToCodeGen(const std::string& op_list_path) {
diff --git a/paddle/fluid/eager/auto_code_generator/op_list.txt b/paddle/fluid/eager/auto_code_generator/op_list.txt
index 2456a7a1846d1e..699a84169d7002 100644
--- a/paddle/fluid/eager/auto_code_generator/op_list.txt
+++ b/paddle/fluid/eager/auto_code_generator/op_list.txt
@@ -1,7 +1,3 @@
-sigmoid
-matmul_v2
-reduce_sum
-elementwise_add
rsqrt
multihead_matmul
addmm
@@ -19,7 +15,9 @@ pow2_decay_with_linear_warmup
split
fc
clear_float_status
+matmul_v2
load
+c_embedding
elementwise_max
adadelta
chunk_eval
@@ -43,8 +41,10 @@ expand_v2
lgamma
solve
deformable_psroi_pooling
+transfer_layout
instance_norm
decode_jpeg
+distributed_push_sparse
gather_nd
reduce_prod
matrix_rank
@@ -57,10 +57,12 @@ sequence_slice
lookup_table
softplus
depthwise_conv2d
+c_allreduce_sum
fused_fc_elementwise_layernorm
sigmoid_cross_entropy_with_logits
exp
scatter
+c_allreduce_min
equal_all
searchsorted
fusion_squared_mat_sub
@@ -73,6 +75,7 @@ momentum
temporal_shift
nce
mv
+global_scatter
proximal_gd
memcpy_h2d
add_position_encoding
@@ -90,13 +93,18 @@ randperm
sequence_scatter
partial_sum
relu6
+partial_allgather
+c_scatter
+alltoall
conv3d
lstm_unit
not_equal
transpose2
+c_sync_comm_stream
uniform_random_batch_size_like
unfold
lrn
+isclose
softmax_with_cross_entropy
isfinite_v2
bernoulli
@@ -105,6 +113,7 @@ gaussian_random
flatten2
matmul
cvm
+recv_v2
adamax
masked_select
range
@@ -112,6 +121,7 @@ bitwise_not
trace
multinomial
modified_huber_loss
+c_reduce_prod
roll
squared_l2_distance
conv3d_transpose
@@ -128,8 +138,10 @@ multiclass_nms2
bpr_loss
fft_c2c
bicubic_interp_v2
+angle
reshape
coalesce_tensor
+dgc
roi_align
reshape2
reduce_any
@@ -139,6 +151,7 @@ sequence_reshape
bilateral_slice
fill_any_like
empty
+partial_recv
pad_constant_like
pool2d
size
@@ -148,11 +161,14 @@ stack
dgc_momentum
lamb
generate_proposals_v2
+c_sync_calc_stream
bitwise_or
gru_unit
fake_channel_wise_quantize_dequantize_abs_max
sampling_id
unsqueeze2
+transfer_dtype
+allreduce
average_accumulates
sequence_enumerate
fusion_seqconv_eltadd_relu
@@ -160,6 +176,7 @@ bce_loss
generate_proposal_labels
im2sequence
isinf
+c_reducescatter
adagrad
linear_chain_crf
retinanet_target_assign
@@ -170,6 +187,7 @@ lookup_table_v2
detection_map
l1_norm
sqrt
+partial_send
fused_elemwise_activation
slogdeterminant
share_buffer
@@ -191,7 +209,10 @@ linear_interp
auc
logical_or
batch_norm
+c_reduce_sum
+elementwise_add
acos
+send_and_recv
unpool
cumprod
sample_logits
@@ -206,6 +227,7 @@ matrix_power
greater_equal
generate_proposals
bilinear_interp
+sigmoid
inplace_abn
softshrink
mul
@@ -243,6 +265,8 @@ overlap_add
fill_constant_batch_size_like
fill_any
dequantize_log
+c_split
+barrier
max_pool2d_with_index
pad3d
norm
@@ -258,6 +282,7 @@ pow
stanh
label_smooth
merged_momentum
+c_reduce_min
ascend_trigger
fused_feedforward
rpn_target_assign
@@ -271,6 +296,7 @@ frame
bincount
shape
group_norm
+c_softmax_with_cross_entropy
resnet_unit
sequence_expand_as
cos_sim
@@ -319,6 +345,7 @@ adamw
elementwise_pow
prior_box
p_norm
+c_concat
unique_consecutive
lod_reset
pad
@@ -339,6 +366,7 @@ pad2d
inverse
spectral_norm
shuffle_channel
+send_v2
psroi_pool
seed
ceil
@@ -347,6 +375,7 @@ reduce_min
cos
ncclAllReduce
cudnn_lstm
+reduce_sum
digamma
assign_value
increment
@@ -366,6 +395,8 @@ atan
less_than
unsqueeze
crf_decoding
+global_gather
+c_allreduce_prod
log_softmax
ftrl
matrix_nms
@@ -374,6 +405,7 @@ cast
tanh_shrink
hard_shrink
multiclass_nms
+c_broadcast
fusion_transpose_flatten_concat
sequence_unpad
fused_elemwise_add_activation
@@ -393,6 +425,7 @@ alloc_float_status
sequence_concat
fusion_seqpool_cvm_concat
similarity_focus
+c_allreduce_max
argsort
sequence_expand
sgd
@@ -413,6 +446,7 @@ pyramid_hash
fake_quantize_dequantize_moving_average_abs_max
multi_dot
sequence_pool
+broadcast
transpose
top_k
dist
@@ -466,10 +500,13 @@ squared_l2_norm
elementwise_sub
margin_rank_loss
faster_tokenizer
+c_identity
+c_reduce_max
relu
is_empty
reduce_all
edit_distance
+distributed_lookup_table
bmm
yolo_box
soft_relu
@@ -484,6 +521,7 @@ nearest_interp
gather
trilinear_interp_v2
box_clip
+c_allgather
isnan_v2
softmax
conv2d_fusion