diff options
Diffstat (limited to 'src/silx/opencl/convolution.py')
| -rw-r--r-- | src/silx/opencl/convolution.py | 95 |
1 files changed, 49 insertions, 46 deletions
diff --git a/src/silx/opencl/convolution.py b/src/silx/opencl/convolution.py index 481e8fb..99ecd02 100644 --- a/src/silx/opencl/convolution.py +++ b/src/silx/opencl/convolution.py @@ -1,7 +1,7 @@ #!/usr/bin/env python # /*########################################################################## # -# Copyright (c) 2019 European Synchrotron Radiation Facility +# Copyright (c) 2019-2023 European Synchrotron Radiation Facility # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal @@ -29,20 +29,30 @@ __license__ = "MIT" __date__ = "01/08/2019" import numpy as np -from copy import copy # python2 from .common import pyopencl as cl import pyopencl.array as parray from .processing import OpenclProcessing, EventDescription from .utils import ConvolutionInfos + class Convolution(OpenclProcessing): """ A class for performing convolution on CPU/GPU with OpenCL. """ - def __init__(self, shape, kernel, axes=None, mode=None, ctx=None, - devicetype="all", platformid=None, deviceid=None, - profile=False, extra_options=None): + def __init__( + self, + shape, + kernel, + axes=None, + mode=None, + ctx=None, + devicetype="all", + platformid=None, + deviceid=None, + profile=False, + extra_options=None, + ): """Constructor of OpenCL Convolution. :param shape: shape of the array. @@ -70,9 +80,14 @@ class Convolution(OpenclProcessing): "allocate_tmp_array": True, "dont_use_textures": False, """ - OpenclProcessing.__init__(self, ctx=ctx, devicetype=devicetype, - platformid=platformid, deviceid=deviceid, - profile=profile) + OpenclProcessing.__init__( + self, + ctx=ctx, + devicetype=devicetype, + platformid=platformid, + deviceid=deviceid, + profile=profile, + ) self._configure_extra_options(extra_options) self._determine_use_case(shape, kernel, axes) @@ -88,7 +103,7 @@ class Convolution(OpenclProcessing): } extra_opts = extra_options or {} self.extra_options.update(extra_opts) - self.use_textures = not(self.extra_options["dont_use_textures"]) + self.use_textures = not (self.extra_options["dont_use_textures"]) self.use_textures &= self.check_textures_availability() def _get_dimensions(self, shape, kernel): @@ -133,8 +148,7 @@ class Convolution(OpenclProcessing): if axes in convol_infos.allowed_axes[uc_name]: self.use_case_name = uc_name self.use_case_desc = uc_params["name"] - #~ self.use_case_kernels = uc_params["kernels"].copy() - self.use_case_kernels = copy(uc_params["kernels"]) # TODO use the above line once we get rid of python2 + self.use_case_kernels = uc_params["kernels"].copy() if self.use_case_name is None: raise ValueError( "Cannot find a use case for data ndim = %d, kernel ndim = %d and axes=%s" @@ -143,8 +157,7 @@ class Convolution(OpenclProcessing): # TODO implement this use case if self.use_case_name == "batched_separable_2D_1D_3D": raise NotImplementedError( - "The use case %s is not implemented" - % self.use_case_name + "The use case %s is not implemented" % self.use_case_name ) # self.axes = axes @@ -168,7 +181,7 @@ class Convolution(OpenclProcessing): "allocate_tmp_array": "data_tmp", } # Nonseparable transforms do not need tmp array - if not(self.separable): + if not (self.separable): self.extra_options["allocate_tmp_array"] = False # Allocate arrays for option_name, array_name in option_array_names.items(): @@ -182,7 +195,7 @@ class Convolution(OpenclProcessing): if isinstance(self.kernel, np.ndarray): self.d_kernel = parray.to_device(self.queue, self.kernel) else: - if not(isinstance(self.kernel, parray.Array)): + if not (isinstance(self.kernel, parray.Array)): raise ValueError("kernel must be either numpy array or pyopencl array") self.d_kernel = self.kernel self._old_input_ref = None @@ -207,7 +220,7 @@ class Convolution(OpenclProcessing): % (self.mode, str(mp.keys())) ) # TODO - if not(self.use_textures) and self.mode.lower() == "constant": + if not (self.use_textures) and self.mode.lower() == "constant": raise NotImplementedError( "mode='constant' is not implemented without textures yet" ) @@ -228,28 +241,30 @@ class Convolution(OpenclProcessing): compile_options = [str("-DUSED_CONV_MODE=%d" % self._c_conv_mode)] if self.use_textures: kernel_files = ["convolution_textures.cl"] - compile_options.extend([ - str("-DIMAGE_DIMS=%d" % self.data_ndim), - str("-DFILTER_DIMS=%d" % self.kernel_ndim), - ]) + compile_options.extend( + [ + str("-DIMAGE_DIMS=%d" % self.data_ndim), + str("-DFILTER_DIMS=%d" % self.kernel_ndim), + ] + ) d_kernel_ref = self.d_kernel_tex else: kernel_files = ["convolution.cl"] d_kernel_ref = self.d_kernel.data - self.compile_kernels( - kernel_files=kernel_files, - compile_options=compile_options - ) + self.compile_kernels(kernel_files=kernel_files, compile_options=compile_options) self.ndrange = self.shape[::-1] self.wg = None kernel_args = [ self.queue, - self.ndrange, self.wg, + self.ndrange, + self.wg, None, None, d_kernel_ref, np.int32(self.kernel.shape[0]), - self.Nx, self.Ny, self.Nz + self.Nx, + self.Ny, + self.Nz, ] if self.kernel_ndim == 2: kernel_args.insert(6, np.int32(self.kernel.shape[1])) @@ -263,10 +278,7 @@ class Convolution(OpenclProcessing): if self.separable: if self.data_tmp is not None: self.swap_pattern = { - 2: [ - ("data_in", "data_tmp"), - ("data_tmp", "data_out") - ], + 2: [("data_in", "data_tmp"), ("data_tmp", "data_out")], 3: [ ("data_in", "data_out"), ("data_out", "data_tmp"), @@ -322,14 +334,14 @@ class Convolution(OpenclProcessing): else: raise ValueError("Please provide either arr= or shape=") if ndim < dim_min or ndim > dim_max: - raise ValueError("%s dimensions should be between %d and %d" - % (name, dim_min, dim_max) + raise ValueError( + "%s dimensions should be between %d and %d" % (name, dim_min, dim_max) ) return ndim def _check_array(self, arr): # TODO allow cl.Buffer - if not(isinstance(arr, parray.Array) or isinstance(arr, np.ndarray)): + if not (isinstance(arr, parray.Array) or isinstance(arr, np.ndarray)): raise TypeError("Expected either pyopencl.array.Array or numpy.ndarray") # TODO composition with ImageProcessing/cast if arr.dtype != np.float32: @@ -351,14 +363,12 @@ class Convolution(OpenclProcessing): self.data_in = array data_in_ref = self.data_in if output is not None: - if not(isinstance(output, np.ndarray)): + if not (isinstance(output, np.ndarray)): self._old_output_ref = self.data_out self.data_out = output # Update OpenCL kernel arguments with new array references self.kernel_args = self._configure_kernel_args( - self.kernel_args, - data_in_ref, - self.data_out + self.kernel_args, data_in_ref, self.data_out ) def _separable_convolution(self): @@ -372,9 +382,7 @@ class Convolution(OpenclProcessing): # Batched: one kernel call in total opencl_kernel = self.kernels.get_kernel(self.use_case_kernels[axis]) opencl_kernel_args = self._configure_kernel_args( - self.kernel_args, - input_ref, - output_ref + self.kernel_args, input_ref, output_ref ) ev = opencl_kernel(*opencl_kernel_args) if self.profile: @@ -395,9 +403,7 @@ class Convolution(OpenclProcessing): self.data_out = self._old_output_ref self._old_output_ref = None self.kernel_args = self._configure_kernel_args( - self.kernel_args, - self.data_in, - self.data_out + self.kernel_args, self.data_in, self.data_out ) def _get_output(self, output): @@ -433,7 +439,4 @@ class Convolution(OpenclProcessing): res = self._get_output(output) return res - __call__ = convolve - - |