diff --git a/oneflow/python/nn/modules/dataset.py b/oneflow/python/nn/modules/dataset.py
index 2f18db4721c0688ce53530b6c1ff22a23263e08e..9b3fa9a4b53428523a42d9cb6c55aa162b802530 100644
--- a/oneflow/python/nn/modules/dataset.py
+++ b/oneflow/python/nn/modules/dataset.py
@@ -87,11 +87,16 @@ class OfrecordRawDecoder(Module):
shape: Sequence[int],
dtype: flow.dtype,
dim1_varying_length: bool = False,
+ truncate: bool = False,
auto_zero_padding: bool = False,
name: Optional[str] = None,
):
super().__init__()
-
+ if auto_zero_padding:
+ print(
+ """WARNING: auto_zero_padding has been deprecated, Please use truncate instead.
+ """
+ )
self._op = (
flow.builtin_op("ofrecord_raw_decoder", name)
.Input("in")
@@ -100,7 +105,7 @@ class OfrecordRawDecoder(Module):
.Attr("shape", shape)
.Attr("data_type", dtype)
.Attr("dim1_varying_length", dim1_varying_length)
- .Attr("auto_zero_padding", auto_zero_padding)
+ .Attr("truncate", truncate or auto_zero_padding)
.Build()
)
@@ -424,11 +429,22 @@ def raw_decoder(
shape: Sequence[int],
dtype: flow.dtype,
dim1_varying_length: bool = False,
+ truncate: bool = False,
auto_zero_padding: bool = False,
name: Optional[str] = None,
):
+ if auto_zero_padding:
+ print(
+ """WARNING: auto_zero_padding has been deprecated, Please use truncate instead.
+ """
+ )
return OfrecordRawDecoder(
- blob_name, shape, dtype, dim1_varying_length, auto_zero_padding, name
+ blob_name,
+ shape,
+ dtype,
+ dim1_varying_length,
+ truncate or auto_zero_padding,
+ name,
).forward(input_record)
diff --git a/oneflow/python/ops/data_ops.py b/oneflow/python/ops/data_ops.py
index 6b0efed51487a83afa55357777a4968d4350a187..a640a2582420f2b7ba724f8ab6ae0b42c06d8837 100644
--- a/oneflow/python/ops/data_ops.py
+++ b/oneflow/python/ops/data_ops.py
@@ -94,8 +94,13 @@ class ImageCodec(object):
@oneflow_export("data.RawCodec")
class RawCodec(object):
- def __init__(self, auto_zero_padding: bool = False) -> None:
- self.auto_zero_padding = auto_zero_padding
+ def __init__(self, truncate: bool = False, auto_zero_padding: bool = False) -> None:
+ if auto_zero_padding:
+ print(
+ """WARNING: auto_zero_padding has been deprecated, Please use truncate instead.
+ """
+ )
+ self.truncate = truncate or auto_zero_padding
@oneflow_export("data.NormByChannelPreprocessor")
@@ -183,7 +188,7 @@ class BlobConf(object):
blob_name=self.name,
shape=self.shape,
dtype=self.dtype,
- auto_zero_padding=self.codec.auto_zero_padding,
+ truncate=self.codec.truncate,
)
return raw
else:
diff --git a/oneflow/python/ops/user_data_ops.py b/oneflow/python/ops/user_data_ops.py
index 41fcfbc1cd7bdd3868ff1324828d88394e0b1d7f..37549b64646822f71aeea5fb5a445fa1ad9b26b7 100644
--- a/oneflow/python/ops/user_data_ops.py
+++ b/oneflow/python/ops/user_data_ops.py
@@ -34,9 +34,15 @@ def OFRecordRawDecoder(
shape: Sequence[int],
dtype: flow.dtype,
dim1_varying_length: bool = False,
+ truncate: bool = False,
auto_zero_padding: bool = False,
name: Optional[str] = None,
) -> oneflow._oneflow_internal.BlobDesc:
+ if auto_zero_padding:
+ print(
+ """WARNING: auto_zero_padding has been deprecated, Please use truncate instead.
+ """
+ )
if name is None:
name = id_util.UniqueStr("OFRecordRawDecoder_")
return (
@@ -48,7 +54,7 @@ def OFRecordRawDecoder(
.Attr("shape", shape)
.Attr("data_type", dtype)
.Attr("dim1_varying_length", dim1_varying_length)
- .Attr("auto_zero_padding", auto_zero_padding)
+ .Attr("truncate", truncate or auto_zero_padding)
.Build()
.InferAndTryRun()
.RemoteBlobList()[0]
diff --git a/oneflow/user/kernels/ofrecord_decoder_kernels.cpp b/oneflow/user/kernels/ofrecord_decoder_kernels.cpp
index 0e323d26b03636a9acd4a1a737821b5d3a5c478d..d59fe8d36a904102ea9e4618de4c02a0cd704db2 100644
--- a/oneflow/user/kernels/ofrecord_decoder_kernels.cpp
+++ b/oneflow/user/kernels/ofrecord_decoder_kernels.cpp
@@ -33,8 +33,8 @@ namespace oneflow {
namespace {
template<typename T>
-void DecodeOneRawOFRecord(const Feature& feature, T* dptr, int64_t sample_elem_cnt,
- bool dim1_varying_length, bool auto_zero_padding) {
+void DecodeOneRawOFRecord(const Feature& feature, T* dptr, int64_t sample_elem_cnt, bool truncate,
+ bool dim1_varying_length) {
if (feature.has_bytes_list()) {
CHECK_EQ(feature.bytes_list().value_size(), 1);
const auto& value0 = feature.bytes_list().value(0);
@@ -42,21 +42,24 @@ void DecodeOneRawOFRecord(const Feature& feature, T* dptr, int64_t sample_elem_c
sample_elem_cnt = std::min<int64_t>(sample_elem_cnt, value0.size());
CopyElem<int8_t, T>(in_dptr, dptr, sample_elem_cnt);
}
-#define DEFINE_ONE_ELIF(PbT, CppT) \
- else if (feature.has_##PbT##_list()) { \
- const auto& list = feature.PbT##_list(); \
- const CppT* in_dptr = list.value().data(); \
- const int64_t padding_elem_num = auto_zero_padding ? sample_elem_cnt - list.value_size() : 0; \
- if (dim1_varying_length || auto_zero_padding) { \
- CHECK_LE(list.value_size(), sample_elem_cnt); \
- sample_elem_cnt = list.value_size(); \
- } else { \
- CHECK_EQ(sample_elem_cnt, list.value_size()); \
- } \
- CopyElem<CppT, T>(in_dptr, dptr, sample_elem_cnt); \
- if (padding_elem_num > 0) { \
- std::memset(dptr + sample_elem_cnt, 0, padding_elem_num * sizeof(T)); \
- } \
+#define DEFINE_ONE_ELIF(PbT, CppT) \
+ else if (feature.has_##PbT##_list()) { \
+ const auto& list = feature.PbT##_list(); \
+ const CppT* in_dptr = list.value().data(); \
+ const int64_t padding_elem_num = truncate ? sample_elem_cnt - list.value_size() : 0; \
+ if (truncate) { \
+ sample_elem_cnt = std::min<int64_t>(sample_elem_cnt, list.value_size()); \
+ } else { \
+ if (dim1_varying_length) { \
+ sample_elem_cnt = list.value_size(); \
+ } else { \
+ CHECK_EQ(sample_elem_cnt, list.value_size()); \
+ } \
+ } \
+ CopyElem<CppT, T>(in_dptr, dptr, sample_elem_cnt); \
+ if (padding_elem_num > 0) { \
+ std::memset(dptr + sample_elem_cnt, 0, padding_elem_num * sizeof(T)); \
+ } \
}
DEFINE_ONE_ELIF(float, float)
DEFINE_ONE_ELIF(double, double)
@@ -88,7 +91,7 @@ class OFRecordRawDecoderKernel final : public user_op::OpKernel {
T* out_dptr = out_blob->mut_dptr<T>();
const std::string& name = ctx->Attr<std::string>("name");
- bool auto_zero_padding = ctx->Attr<bool>("auto_zero_padding");
+ bool truncate = ctx->Attr<bool>("truncate");
bool dim1_varying_length = ctx->Attr<bool>("dim1_varying_length");
MultiThreadLoop(record_num, [&](size_t i) {
@@ -97,7 +100,7 @@ class OFRecordRawDecoderKernel final : public user_op::OpKernel {
CHECK(record.feature().find(name) != record.feature().end())
<< "Field " << name << " not found";
const Feature& feature = record.feature().at(name);
- DecodeOneRawOFRecord(feature, dptr, sample_elem_cnt, auto_zero_padding, dim1_varying_length);
+ DecodeOneRawOFRecord(feature, dptr, sample_elem_cnt, truncate, dim1_varying_length);
});
}
bool AlwaysComputeWhenAllOutputsEmpty() const override { return false; }
diff --git a/oneflow/user/ops/ofrecord_decoder_ops.cpp b/oneflow/user/ops/ofrecord_decoder_ops.cpp
index 1250fe4743e9a5df06af20a925fb7ced196ff087..2fa02969bff2684fb19c247c2f2b8628be84b82a 100644
--- a/oneflow/user/ops/ofrecord_decoder_ops.cpp
+++ b/oneflow/user/ops/ofrecord_decoder_ops.cpp
@@ -25,7 +25,7 @@ REGISTER_NO_GRAD_CPU_ONLY_USER_OP("ofrecord_raw_decoder")
.Attr<Shape>("shape")
.Attr<DataType>("data_type")
.Attr<bool>("dim1_varying_length", false)
- .Attr<bool>("auto_zero_padding", false)
+ .Attr<bool>("truncate", false)
.SetTensorDescInferFn([](user_op::InferContext* ctx) -> Maybe<void> {
const user_op::TensorDesc& in_tensor = ctx->InputTensorDesc("in", 0);
user_op::TensorDesc* out_tensor = ctx->OutputTensorDesc("out", 0);