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Update to remove 8S and include QX as data type.
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@liuliu
liuliu committed Sep 2, 2023
1 parent 5d2bc07 commit df62221
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Showing 5 changed files with 22 additions and 22 deletions.
4 changes: 2 additions & 2 deletions lib/ccv.h
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Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,7 @@ enum {
CCV_64S = 0x08000,
CCV_64F = 0x10000,
CCV_16F = 0x20000,
CCV_8S = 0x40000, // We can still squeeze in 1 more type, which probably will be 8F. (0xFF000 are for data types).
CCV_QX = 0x40000, // QX is a catch-all for quantized models (anything less than or equal to 1-byte). We can still squeeze in 1 more primitive type, which probably will be 8F or BF16. (0xFF000 are for data types).
};

enum {
Expand All @@ -74,7 +74,7 @@ static const ssize_t _ccv_get_data_type_size[] = {
#define CCV_MAX_CHANNEL (0xFFF)
#define CCV_GET_CHANNEL(x) ((x) & 0xFFF)
#define CCV_GET_STEP(cols, type) (((cols) * CCV_GET_DATA_TYPE_SIZE(type) * CCV_GET_CHANNEL(type) + 3) & -4)
#define CCV_ALL_DATA_TYPE (CCV_8U | CCV_32S | CCV_32F | CCV_64S | CCV_64F | CCV_16F | CCV_8S)
#define CCV_ALL_DATA_TYPE (CCV_8U | CCV_32S | CCV_32F | CCV_64S | CCV_64F | CCV_16F | CCV_QX)

enum {
CCV_MATRIX_DENSE = 0x00100000,
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8 changes: 4 additions & 4 deletions lib/nnc/ccv_nnc_cmd.c
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Original file line number Diff line number Diff line change
Expand Up @@ -362,10 +362,10 @@ ccv_nnc_cmd_t ccv_nnc_cmd_autotune(const ccv_nnc_cmd_t cmd, const size_t max_wor
int tensor_memory = 0, tensor_formats = 0, tensor_datatypes = 0;
for (i = 0; i < input_size; i++)
if (inputs[i])
tensor_memory |= CCV_TENSOR_GET_MEMORY(inputs[i]->info.type), tensor_formats |= inputs[i]->info.format, tensor_datatypes |= inputs[i]->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(inputs[i]->info.type), tensor_formats |= inputs[i]->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(inputs[i]->info.datatype);
for (i = 0; i < output_size; i++)
if (outputs[i])
tensor_memory |= CCV_TENSOR_GET_MEMORY(outputs[i]->info.type), tensor_formats |= outputs[i]->info.format, tensor_datatypes |= outputs[i]->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(outputs[i]->info.type), tensor_formats |= outputs[i]->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(outputs[i]->info.datatype);
// In this case, we cannot determine the type of the tensor, skip auto-tune.
if (!tensor_memory)
return cmd;
Expand Down Expand Up @@ -682,10 +682,10 @@ int ccv_nnc_cmd_exec(const ccv_nnc_cmd_t cmd, const ccv_nnc_hint_t hint, const i
int tensor_memory = 0, tensor_formats = 0, tensor_datatypes = 0;
for (i = 0; i < input_size; i++)
if (inputs[i])
tensor_memory |= CCV_TENSOR_GET_MEMORY(inputs[i]->info.type), tensor_formats |= inputs[i]->info.format, tensor_datatypes |= inputs[i]->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(inputs[i]->info.type), tensor_formats |= inputs[i]->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(inputs[i]->info.datatype);
for (i = 0; i < output_size; i++)
if (outputs[i])
tensor_memory |= CCV_TENSOR_GET_MEMORY(outputs[i]->info.type), tensor_formats |= outputs[i]->info.format, tensor_datatypes |= outputs[i]->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(outputs[i]->info.type), tensor_formats |= outputs[i]->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(outputs[i]->info.datatype);
backend = ccv_nnc_cmd_find_backend(cmd, tensor_memory, tensor_formats, tensor_datatypes);
}
assert(backend != CCV_NNC_NO_BACKEND);
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4 changes: 2 additions & 2 deletions lib/nnc/ccv_nnc_graph.c
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Original file line number Diff line number Diff line change
Expand Up @@ -352,7 +352,7 @@ void ccv_nnc_graph_exec_set_io(ccv_nnc_graph_t* const graph, const ccv_nnc_graph
if (info->inputs[i])
{
ccv_nnc_tensor_t* const tensor = CCV_IS_TENSOR_MULTIVIEW(info->inputs[i]) ? _ccv_nnc_any_tensor_from_tensor_multiview((ccv_nnc_tensor_multiview_t*)info->inputs[i]) : info->inputs[i];
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor->info.type), tensor_formats |= tensor->info.format, tensor_datatypes |= tensor->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor->info.type), tensor_formats |= tensor->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(tensor->info.datatype);
}
info->cmd.backend = ccv_nnc_cmd_find_backend(info->cmd, tensor_memory, tensor_formats, tensor_datatypes);
info->input_size = input_size;
Expand Down Expand Up @@ -415,7 +415,7 @@ ccv_nnc_graph_exec_t ccv_nnc_graph_exec_new(ccv_nnc_graph_t* const graph, const
if (info.inputs[i])
{
ccv_nnc_tensor_t* const tensor = CCV_IS_TENSOR_MULTIVIEW(info.inputs[i]) ? _ccv_nnc_any_tensor_from_tensor_multiview((ccv_nnc_tensor_multiview_t*)info.inputs[i]) : info.inputs[i];
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor->info.type), tensor_formats |= tensor->info.format, tensor_datatypes |= tensor->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor->info.type), tensor_formats |= tensor->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(tensor->info.datatype);
}
info.cmd.backend = ccv_nnc_cmd_find_backend(info.cmd, tensor_memory, tensor_formats, tensor_datatypes);
}
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4 changes: 2 additions & 2 deletions lib/nnc/ccv_nnc_symbolic_graph.c
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Original file line number Diff line number Diff line change
Expand Up @@ -838,7 +838,7 @@ static void _ccv_nnc_graph_exec_symbol_set_io(ccv_nnc_symbolic_graph_t* const gr
{
const ccv_nnc_tensor_symbol_info_t* const tensor_info = (ccv_nnc_tensor_symbol_info_t*)ccv_array_get(graph->tensor_symbol_info, d);
tensor_auto = tensor_auto || ccv_nnc_is_tensor_auto(tensor_info->info);
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor_info->info.type), tensor_formats |= tensor_info->info.format, tensor_datatypes |= tensor_info->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor_info->info.type), tensor_formats |= tensor_info->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(tensor_info->info.datatype);
}
}
for (i = 0; i < output_size; i++)
Expand All @@ -849,7 +849,7 @@ static void _ccv_nnc_graph_exec_symbol_set_io(ccv_nnc_symbolic_graph_t* const gr
{
const ccv_nnc_tensor_symbol_info_t* const tensor_info = (ccv_nnc_tensor_symbol_info_t*)ccv_array_get(graph->tensor_symbol_info, d);
tensor_auto = tensor_auto || ccv_nnc_is_tensor_auto(tensor_info->info);
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor_info->info.type), tensor_formats |= tensor_info->info.format, tensor_datatypes |= tensor_info->info.datatype;
tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor_info->info.type), tensor_formats |= tensor_info->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(tensor_info->info.datatype);
}
}
// If there is no auto tensor, we try to find backend (we don't know which backend if the tensor is auto).
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24 changes: 12 additions & 12 deletions lib/nnc/ccv_nnc_tensor.c
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Original file line number Diff line number Diff line change
Expand Up @@ -26,11 +26,11 @@ ccv_nnc_tensor_t* ccv_nnc_tensor_new(const void* const ptr, const ccv_nnc_tensor
tensor->info = params;
if (tfb)
{
tensor->type = CCV_NO_DATA_ALLOC | CCV_MATRIX_DENSE | params.datatype | params.dim[2];
tensor->type = CCV_NO_DATA_ALLOC | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype) | params.dim[2];
// This corresponding to mat->step
tensor->info.dim[4] = CCV_GET_STEP(params.dim[1], (params.datatype | params.dim[2]));
tensor->info.dim[4] = CCV_GET_STEP(params.dim[1], (CCV_GET_DATA_TYPE(params.datatype) | params.dim[2]));
} else // This won't be recognized by ccv_dense_matrix_t
tensor->type = CCV_NO_DATA_ALLOC | CCV_MATRIX_DENSE | params.datatype;
tensor->type = CCV_NO_DATA_ALLOC | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype);
tensor->data.u8 = (uint8_t*)ptr;
return tensor;
}
Expand Down Expand Up @@ -77,11 +77,11 @@ ccv_nnc_tensor_t* ccv_nnc_tensor_new(const void* const ptr, const ccv_nnc_tensor
tensor->info = params;
if (tfb)
{
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | params.datatype | params.dim[2];
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype) | params.dim[2];
// This corresponding to mat->step
tensor->info.dim[4] = CCV_GET_STEP(params.dim[1], (params.datatype | params.dim[2]));
tensor->info.dim[4] = CCV_GET_STEP(params.dim[1], (CCV_GET_DATA_TYPE(params.datatype) | params.dim[2]));
} else
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | params.datatype;
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype);
return tensor;
}

Expand All @@ -100,11 +100,11 @@ ccv_nnc_tensor_t* ccv_nnc_tensor_resize(ccv_nnc_tensor_t* const tensor, const cc
#endif
if (tfb)
{
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | params.datatype | params.dim[2];
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype) | params.dim[2];
// This corresponding to mat->step
tensor->info.dim[4] = CCV_GET_STEP(params.dim[1], (params.datatype | params.dim[2]));
tensor->info.dim[4] = CCV_GET_STEP(params.dim[1], (CCV_GET_DATA_TYPE(params.datatype) | params.dim[2]));
} else
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | params.datatype;
tensor->type = CCV_UNMANAGED | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype);
if (size <= tensor->data_size) // Nothing.
{
#ifdef HAVE_CUDA
Expand Down Expand Up @@ -177,11 +177,11 @@ ccv_nnc_tensor_t ccv_nnc_tensor(const void* const ptr, const ccv_nnc_tensor_para
}
if (tfb)
{
tensor.type = CCV_NO_DATA_ALLOC | CCV_UNMANAGED | CCV_MATRIX_DENSE | params.datatype | params.dim[2];
tensor.type = CCV_NO_DATA_ALLOC | CCV_UNMANAGED | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype) | params.dim[2];
// This corresponding to mat->step
tensor.info.dim[4] = CCV_GET_STEP(params.dim[1], (params.datatype | params.dim[2]));
tensor.info.dim[4] = CCV_GET_STEP(params.dim[1], (CCV_GET_DATA_TYPE(params.datatype) | params.dim[2]));
} else // This won't be recognized by ccv_dense_matrix_t
tensor.type = CCV_NO_DATA_ALLOC | CCV_UNMANAGED | CCV_MATRIX_DENSE | params.datatype;
tensor.type = CCV_NO_DATA_ALLOC | CCV_UNMANAGED | CCV_MATRIX_DENSE | CCV_GET_DATA_TYPE(params.datatype);
tensor.data.u8 = (uint8_t*)ptr;
tensor.data_size = 0;
return tensor;
Expand Down

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