validation.cuda#
C API#
cuda_example_py#
- class onnx_extended.validation.cuda.cuda_example_py.FpemuMode#
Available option for parameter mode in function fpemu_cuda_forward.
Members:
E4M3_RNE
- property name#
- onnx_extended.validation.cuda.cuda_example_py.cuda_device_count() int#
Returns the number of cuda devices.
- onnx_extended.validation.cuda.cuda_example_py.cuda_device_memory(device: int = 0) tuple#
Returns the free and total memory for a particular device.
- onnx_extended.validation.cuda.cuda_example_py.cuda_devices_memory() list#
Returns the free and total memory for all devices.
- onnx_extended.validation.cuda.cuda_example_py.cuda_version() int#
Returns the CUDA version the project was compiled with.
- onnx_extended.validation.cuda.cuda_example_py.fpemu_cuda_forward(input: numpy.ndarray[numpy.float32], mode: onnx_extended.validation.cuda.cuda_example_py.FpemuMode = <FpemuMode.E4M3_RNE: 1>, inplace: bool = False, scale: float = 1.0, block_norm: bool = False, block_size: int = 1, cuda_device: int = 0) numpy.ndarray[numpy.float32]#
Experimental
- Parameters:
input – array
mode – which quantization type
inplace – modification inplace instead of a new outoput
scale – scale
block_norm – normalization accrocess blocks
block_size – block size
cuda_device – device id (if mulitple one)
- Returns:
forward pass
- onnx_extended.validation.cuda.cuda_example_py.gemm_benchmark_test(test_id: int = 0, N: int = 10, m: int = 16, n: int = 16, k: int = 16, lda: int = 16, ldb: int = 16, ldd: int = 16) Dict[str, float]
Benchmark Gemm on CUDA
- Parameters:
test_id – a test configuration (int)
N – number of repetitions
m – dimensions of the matrices
n – dimensions of the matrices
k – dimensions of the matrices
lda – leading dimension of A
ldb – leading dimension of B
ldd – leading dimension of the result
- Returns:
metrics in a dictionary
cuda_monitor#
- onnx_extended.validation.cuda.cuda_monitor.cuda_version() int#
Returns the CUDA version the project was compiled with.
- onnx_extended.validation.cuda.cuda_monitor.nvml_device_get_count() int#
Returns the number of GPU units.
- onnx_extended.validation.cuda.cuda_monitor.nvml_device_get_memory_info(device: int = 0) tuple#
Returns the free memory, the used memory, the total memory for a GPU device.