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Merged
merged 6 commits into from
Feb 28, 2021
Merged

dlpack v0.4 #614

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38ba650
dlpack v0.4
Feb 21, 2021
7737b22
fixed onnx
Feb 21, 2021
a147e1b
Merge branch 'master' into dlpack_v0.4
Feb 23, 2021
1cb54a3
Merge branch 'master' into dlpack_v0.4
Feb 24, 2021
ec2b615
Merge branch 'master' into dlpack_v0.4
Feb 24, 2021
253860d
Merge branch 'master' into dlpack_v0.4
Feb 25, 2021
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2 changes: 1 addition & 1 deletion get_deps.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@ MKL=mkl
ONNXRUNTIME=onnxruntime

######################################################################################## DLPACK
DLPACK_VERSION="v0.3"
DLPACK_VERSION="v0.4"
if [[ $WITH_DLPACK != 0 ]]; then
[[ $FORCE == 1 ]] && rm -rf $DLPACK

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4 changes: 2 additions & 2 deletions src/backends/onnxruntime.c
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Expand Up @@ -172,7 +172,7 @@ RAI_Tensor *RAI_TensorCreateFromOrtValue(OrtValue *v, size_t batch_offset, long

ret = RAI_TensorNew();

DLContext ctx = (DLContext){.device_type = kDLCPU, .device_id = 0};
DLDevice device = (DLDevice){.device_type = kDLCPU, .device_id = 0};

OrtTensorTypeAndShapeInfo *info;
status = ort->GetTensorTypeAndShape(v, &info);
Expand Down Expand Up @@ -243,7 +243,7 @@ RAI_Tensor *RAI_TensorCreateFromOrtValue(OrtValue *v, size_t batch_offset, long
// TODO: use manager_ctx to ensure ORT tensor doesn't get deallocated
// This applies to outputs

ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.ctx = ctx,
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.device = device,
#ifdef RAI_COPY_RUN_OUTPUT
.data = data,
#else
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4 changes: 2 additions & 2 deletions src/backends/tensorflow.c
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Expand Up @@ -90,7 +90,7 @@ RAI_Tensor *RAI_TensorCreateFromTFTensor(TF_Tensor *tensor, size_t batch_offset,
long long batch_size) {
RAI_Tensor *ret = RAI_TensorNew();

DLContext ctx = (DLContext){.device_type = kDLCPU, .device_id = 0};
DLDevice device = (DLDevice){.device_type = kDLCPU, .device_id = 0};

const size_t ndims = TF_NumDims(tensor);

Expand Down Expand Up @@ -129,7 +129,7 @@ RAI_Tensor *RAI_TensorCreateFromTFTensor(TF_Tensor *tensor, size_t batch_offset,
// This applies to outputs

ret->tensor = (DLManagedTensor){
.dl_tensor = (DLTensor){.ctx = ctx,
.dl_tensor = (DLTensor){.device = device,
#ifdef RAI_COPY_RUN_OUTPUT
.data = data,
#else
Expand Down
19 changes: 7 additions & 12 deletions src/libtflite_c/tflite_c.cpp
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Expand Up @@ -48,16 +48,11 @@ static DLDataType getDLDataType(const TfLiteTensor *tensor) {
return dtype;
}

static DLContext getDLContext(const TfLiteTensor *tensor, const int64_t &device_id) {
DLContext ctx;
ctx.device_id = device_id;
// if (tensor->.is_cuda()) {
// ctx.device_type = DLDeviceType::kDLGPU;
// } else {
// ctx.device_type = DLDeviceType::kDLCPU;
// }
ctx.device_type = DLDeviceType::kDLCPU;
return ctx;
static DLDevice getDLDevice(const TfLiteTensor *tensor, const int64_t &device_id) {
DLDevice device;
device.device_id = device_id;
device.device_type = DLDeviceType::kDLCPU;
return device;
}

#if 0
Expand Down Expand Up @@ -139,10 +134,10 @@ DLManagedTensor *toManagedDLPack(std::shared_ptr<tflite::Interpreter> interprete
DLDataType dtype = getDLDataType(tensor);

int64_t device_id = 0;
DLContext ctx = getDLContext(tensor, device_id);
DLDevice device = getDLDevice(tensor, device_id);

DLTensor dl_tensor = (DLTensor){.data = new uint8_t[tensor->bytes],
.ctx = ctx,
.device = device,
.ndim = output_dims->size,
.dtype = dtype,
.shape = new int64_t[output_dims->size],
Expand Down
16 changes: 8 additions & 8 deletions src/libtorch_c/torch_c.cpp
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Expand Up @@ -64,15 +64,15 @@ static DLDataType getDLDataType(const at::Tensor &t) {
return dtype;
}

static DLContext getDLContext(const at::Tensor &tensor, const int64_t &device_id) {
DLContext ctx;
ctx.device_id = device_id;
static DLDevice getDLDevice(const at::Tensor &tensor, const int64_t &device_id) {
DLDevice device;
device.device_id = device_id;
if (tensor.is_cuda()) {
ctx.device_type = DLDeviceType::kDLGPU;
device.device_type = DLDeviceType::kDLGPU;
} else {
ctx.device_type = DLDeviceType::kDLCPU;
device.device_type = DLDeviceType::kDLCPU;
}
return ctx;
return device;
}

static at::DeviceType getATenDeviceType(DLDeviceType device_type) {
Expand Down Expand Up @@ -145,7 +145,7 @@ at::ScalarType toScalarType(const DLDataType &dtype) {
}

torch::Tensor fromDLPack(const DLTensor *src) {
at::DeviceType device_type = getATenDeviceType(src->ctx.device_type);
at::DeviceType device_type = getATenDeviceType(src->device.device_type);
at::ScalarType stype = toScalarType(src->dtype);
// torch::Device device(device_type, src->ctx.device_id);
torch::Device device(device_type, -1);
Expand Down Expand Up @@ -176,7 +176,7 @@ DLManagedTensor *toManagedDLPack(const torch::Tensor &src_) {
if (src.is_cuda()) {
device_id = src.get_device();
}
atDLMTensor->tensor.dl_tensor.ctx = getDLContext(src, device_id);
atDLMTensor->tensor.dl_tensor.device = getDLDevice(src, device_id);
atDLMTensor->tensor.dl_tensor.ndim = src.dim();
atDLMTensor->tensor.dl_tensor.dtype = getDLDataType(src);
atDLMTensor->tensor.dl_tensor.shape = const_cast<int64_t *>(src.sizes().data());
Expand Down
12 changes: 6 additions & 6 deletions src/serialization/RDB/decoder/current/v1/decode_v1.c
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Expand Up @@ -12,15 +12,15 @@ void *RAI_RDBLoadTensor_v1(RedisModuleIO *io) {
int64_t *shape = NULL;
int64_t *strides = NULL;

DLContext ctx;
ctx.device_type = RedisModule_LoadUnsigned(io);
ctx.device_id = RedisModule_LoadUnsigned(io);
DLDevice device;
device.device_type = RedisModule_LoadUnsigned(io);
device.device_id = RedisModule_LoadUnsigned(io);
if (RedisModule_IsIOError(io))
goto cleanup;

// For now we only support CPU tensors (except during model and script run)
assert(ctx.device_type == kDLCPU);
assert(ctx.device_id == 0);
assert(device.device_type == kDLCPU);
assert(device.device_id == 0);

DLDataType dtype;
dtype.bits = RedisModule_LoadUnsigned(io);
Expand Down Expand Up @@ -49,7 +49,7 @@ void *RAI_RDBLoadTensor_v1(RedisModuleIO *io) {
goto cleanup;

RAI_Tensor *ret = RAI_TensorNew();
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.ctx = ctx,
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.device = device,
.data = data,
.ndim = ndims,
.dtype = dtype,
Expand Down
12 changes: 6 additions & 6 deletions src/serialization/RDB/decoder/previous/v0/decode_v0.c
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Expand Up @@ -5,15 +5,15 @@ void *RAI_RDBLoadTensor_v0(RedisModuleIO *io) {
int64_t *shape = NULL;
int64_t *strides = NULL;

DLContext ctx;
ctx.device_type = RedisModule_LoadUnsigned(io);
ctx.device_id = RedisModule_LoadUnsigned(io);
DLDevice device;
device.device_type = RedisModule_LoadUnsigned(io);
device.device_id = RedisModule_LoadUnsigned(io);
if (RedisModule_IsIOError(io))
goto cleanup;

// For now we only support CPU tensors (except during model and script run)
assert(ctx.device_type == kDLCPU);
assert(ctx.device_id == 0);
assert(device.device_type == kDLCPU);
assert(device.device_id == 0);

DLDataType dtype;
dtype.bits = RedisModule_LoadUnsigned(io);
Expand Down Expand Up @@ -42,7 +42,7 @@ void *RAI_RDBLoadTensor_v0(RedisModuleIO *io) {
goto cleanup;

RAI_Tensor *ret = RAI_TensorNew();
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.ctx = ctx,
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.device = device,
.data = data,
.ndim = ndims,
.dtype = dtype,
Expand Down
4 changes: 2 additions & 2 deletions src/serialization/RDB/encoder/v1/encode_v1.c
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Expand Up @@ -5,8 +5,8 @@ void RAI_RDBSaveTensor_v1(RedisModuleIO *io, void *value) {

size_t ndim = tensor->tensor.dl_tensor.ndim;

RedisModule_SaveUnsigned(io, tensor->tensor.dl_tensor.ctx.device_type);
RedisModule_SaveUnsigned(io, tensor->tensor.dl_tensor.ctx.device_id);
RedisModule_SaveUnsigned(io, tensor->tensor.dl_tensor.device.device_type);
RedisModule_SaveUnsigned(io, tensor->tensor.dl_tensor.device.device_id);
RedisModule_SaveUnsigned(io, tensor->tensor.dl_tensor.dtype.bits);
RedisModule_SaveUnsigned(io, tensor->tensor.dl_tensor.dtype.code);
RedisModule_SaveUnsigned(io, tensor->tensor.dl_tensor.dtype.lanes);
Expand Down
10 changes: 5 additions & 5 deletions src/tensor.c
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Expand Up @@ -123,7 +123,7 @@ RAI_Tensor *RAI_TensorCreateWithDLDataType(DLDataType dtype, long long *dims, in
strides[i] *= strides[i + 1] * shape[i + 1];
}

DLContext ctx = (DLContext){.device_type = kDLCPU, .device_id = 0};
DLDevice device = (DLDevice){.device_type = kDLCPU, .device_id = 0};
void *data = NULL;
switch (tensorAllocMode) {
case TENSORALLOC_ALLOC:
Expand All @@ -140,7 +140,7 @@ RAI_Tensor *RAI_TensorCreateWithDLDataType(DLDataType dtype, long long *dims, in
break;
}

ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.ctx = ctx,
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.device = device,
.data = data,
.ndim = ndims,
.dtype = dtype,
Expand Down Expand Up @@ -185,7 +185,7 @@ RAI_Tensor *_TensorCreateWithDLDataTypeAndRString(DLDataType dtype, size_t dtype
strides[i] *= strides[i + 1] * shape[i + 1];
}

DLContext ctx = (DLContext){.device_type = kDLCPU, .device_id = 0};
DLDevice device = (DLDevice){.device_type = kDLCPU, .device_id = 0};
size_t nbytes = len * dtypeSize;

size_t blob_len;
Expand All @@ -201,7 +201,7 @@ RAI_Tensor *_TensorCreateWithDLDataTypeAndRString(DLDataType dtype, size_t dtype
RAI_HoldString(NULL, rstr);

RAI_Tensor *ret = RAI_TensorNew();
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.ctx = ctx,
ret->tensor = (DLManagedTensor){.dl_tensor = (DLTensor){.device = device,
.data = data,
.ndim = ndims,
.dtype = dtype,
Expand Down Expand Up @@ -342,7 +342,7 @@ RAI_Tensor *RAI_TensorCreateFromDLTensor(DLManagedTensor *dl_tensor) {
RAI_Tensor *ret = RAI_TensorNew();

ret->tensor =
(DLManagedTensor){.dl_tensor = (DLTensor){.ctx = dl_tensor->dl_tensor.ctx,
(DLManagedTensor){.dl_tensor = (DLTensor){.device = dl_tensor->dl_tensor.device,
.data = dl_tensor->dl_tensor.data,
.ndim = dl_tensor->dl_tensor.ndim,
.dtype = dl_tensor->dl_tensor.dtype,
Expand Down