1 | """ |
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2 | Core model handling routines. |
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3 | """ |
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4 | from __future__ import print_function |
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5 | |
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6 | __all__ = [ |
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7 | "list_models", "load_model", "load_model_info", |
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8 | "build_model", "precompile_dll", |
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9 | ] |
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10 | |
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11 | import os |
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12 | from os.path import basename, dirname, join as joinpath, splitext |
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13 | from glob import glob |
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14 | |
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15 | import numpy as np # type: ignore |
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16 | |
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17 | from . import generate |
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18 | from . import modelinfo |
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19 | from . import product |
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20 | from . import mixture |
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21 | from . import kernelpy |
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22 | from . import kerneldll |
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23 | try: |
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24 | from . import kernelcl |
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25 | HAVE_OPENCL = True |
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26 | except Exception: |
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27 | HAVE_OPENCL = False |
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28 | |
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29 | try: |
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30 | from typing import List, Union, Optional, Any |
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31 | from .kernel import KernelModel |
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32 | from .modelinfo import ModelInfo |
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33 | except ImportError: |
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34 | pass |
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35 | |
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36 | try: |
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37 | np.meshgrid([]) |
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38 | meshgrid = np.meshgrid |
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39 | except Exception: |
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40 | # CRUFT: np.meshgrid requires multiple vectors |
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41 | def meshgrid(*args): |
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42 | if len(args) > 1: |
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43 | return np.meshgrid(*args) |
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44 | else: |
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45 | return [np.asarray(v) for v in args] |
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46 | |
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47 | # TODO: refactor composite model support |
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48 | # The current load_model_info/build_model does not reuse existing model |
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49 | # definitions when loading a composite model, instead reloading and |
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50 | # rebuilding the kernel for each component model in the expression. This |
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51 | # is fine in a scripting environment where the model is built when the script |
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52 | # starts and is thrown away when the script ends, but may not be the best |
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53 | # solution in a long-lived application. This affects the following functions: |
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54 | # |
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55 | # load_model |
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56 | # load_model_info |
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57 | # build_model |
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58 | |
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59 | def list_models(kind=None): |
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60 | # type: () -> List[str] |
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61 | """ |
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62 | Return the list of available models on the model path. |
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63 | """ |
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64 | KINDS = ("all", "py", "c", "double", "oriented", "magnetic") |
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65 | if kind and kind not in KINDS: |
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66 | raise ValueError("kind not in "+", ".join(KINDS)) |
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67 | root = dirname(__file__) |
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68 | files = sorted(glob(joinpath(root, 'models', "[a-zA-Z]*.py"))) |
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69 | available_models = [basename(f)[:-3] for f in files] |
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70 | selected = [name for name in available_models if _matches(name, kind)] |
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71 | |
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72 | return selected |
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73 | |
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74 | def _matches(name, kind): |
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75 | if kind is None or kind=="all": |
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76 | return True |
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77 | info = load_model_info(name) |
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78 | pars = info.parameters.kernel_parameters |
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79 | if kind == "py" and callable(info.Iq): |
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80 | return True |
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81 | elif kind == "c" and not callable(info.Iq): |
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82 | return True |
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83 | elif kind == "double" and not info.single: |
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84 | return True |
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85 | elif kind == "oriented" and any(p.type=='orientation' for p in pars): |
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86 | return True |
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87 | elif kind == "magnetic" and any(p.type=='sld' for p in pars): |
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88 | return True |
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89 | return False |
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90 | |
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91 | def load_model(model_name, dtype=None, platform='ocl'): |
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92 | # type: (str, str, str) -> KernelModel |
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93 | """ |
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94 | Load model info and build model. |
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95 | |
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96 | *model_name* is the name of the model as used by :func:`load_model_info`. |
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97 | Additional keyword arguments are passed directly to :func:`build_model`. |
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98 | """ |
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99 | return build_model(load_model_info(model_name), |
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100 | dtype=dtype, platform=platform) |
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101 | |
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102 | |
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103 | def load_model_info(model_name): |
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104 | # type: (str) -> modelinfo.ModelInfo |
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105 | """ |
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106 | Load a model definition given the model name. |
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107 | |
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108 | This returns a handle to the module defining the model. This can be |
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109 | used with functions in generate to build the docs or extract model info. |
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110 | """ |
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111 | parts = model_name.split('+') |
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112 | if len(parts) > 1: |
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113 | model_info_list = [load_model_info(p) for p in parts] |
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114 | return mixture.make_mixture_info(model_info_list) |
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115 | |
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116 | parts = model_name.split('*') |
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117 | if len(parts) > 1: |
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118 | if len(parts) > 2: |
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119 | raise ValueError("use P*S to apply structure factor S to model P") |
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120 | P_info, Q_info = [load_model_info(p) for p in parts] |
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121 | return product.make_product_info(P_info, Q_info) |
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122 | |
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123 | kernel_module = generate.load_kernel_module(model_name) |
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124 | return modelinfo.make_model_info(kernel_module) |
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125 | |
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126 | |
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127 | def build_model(model_info, dtype=None, platform="ocl"): |
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128 | # type: (modelinfo.ModelInfo, str, str) -> KernelModel |
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129 | """ |
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130 | Prepare the model for the default execution platform. |
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131 | |
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132 | This will return an OpenCL model, a DLL model or a python model depending |
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133 | on the model and the computing platform. |
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134 | |
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135 | *model_info* is the model definition structure returned from |
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136 | :func:`load_model_info`. |
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137 | |
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138 | *dtype* indicates whether the model should use single or double precision |
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139 | for the calculation. Choices are 'single', 'double', 'quad', 'half', |
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140 | or 'fast'. If *dtype* ends with '!', then force the use of the DLL rather |
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141 | than OpenCL for the calculation. |
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142 | |
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143 | *platform* should be "dll" to force the dll to be used for C models, |
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144 | otherwise it uses the default "ocl". |
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145 | """ |
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146 | composition = model_info.composition |
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147 | if composition is not None: |
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148 | composition_type, parts = composition |
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149 | models = [build_model(p, dtype=dtype, platform=platform) for p in parts] |
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150 | if composition_type == 'mixture': |
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151 | return mixture.MixtureModel(model_info, models) |
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152 | elif composition_type == 'product': |
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153 | from . import product |
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154 | P, S = models |
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155 | return product.ProductModel(model_info, P, S) |
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156 | else: |
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157 | raise ValueError('unknown mixture type %s'%composition_type) |
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158 | |
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159 | # If it is a python model, return it immediately |
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160 | if callable(model_info.Iq): |
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161 | return kernelpy.PyModel(model_info) |
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162 | |
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163 | numpy_dtype, fast, platform = parse_dtype(model_info, dtype, platform) |
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164 | |
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165 | source = generate.make_source(model_info) |
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166 | if platform == "dll": |
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167 | #print("building dll", numpy_dtype) |
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168 | return kerneldll.load_dll(source['dll'], model_info, numpy_dtype) |
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169 | else: |
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170 | #print("building ocl", numpy_dtype) |
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171 | return kernelcl.GpuModel(source, model_info, numpy_dtype, fast=fast) |
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172 | |
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173 | def precompile_dlls(path, dtype="double"): |
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174 | # type: (str, str) -> List[str] |
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175 | """ |
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176 | Precompile the dlls for all builtin models, returning a list of dll paths. |
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177 | |
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178 | *path* is the directory in which to save the dlls. It will be created if |
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179 | it does not already exist. |
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180 | |
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181 | This can be used when build the windows distribution of sasmodels |
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182 | which may be missing the OpenCL driver and the dll compiler. |
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183 | """ |
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184 | numpy_dtype = np.dtype(dtype) |
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185 | if not os.path.exists(path): |
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186 | os.makedirs(path) |
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187 | compiled_dlls = [] |
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188 | for model_name in list_models(): |
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189 | model_info = load_model_info(model_name) |
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190 | if not callable(model_info.Iq): |
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191 | source = generate.make_source(model_info)['dll'] |
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192 | old_path = kerneldll.DLL_PATH |
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193 | try: |
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194 | kerneldll.DLL_PATH = path |
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195 | dll = kerneldll.make_dll(source, model_info, dtype=numpy_dtype) |
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196 | finally: |
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197 | kerneldll.DLL_PATH = old_path |
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198 | compiled_dlls.append(dll) |
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199 | return compiled_dlls |
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200 | |
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201 | def parse_dtype(model_info, dtype=None, platform=None): |
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202 | # type: (ModelInfo, str, str) -> (np.dtype, bool, str) |
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203 | """ |
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204 | Interpret dtype string, returning np.dtype and fast flag. |
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205 | |
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206 | Possible types include 'half', 'single', 'double' and 'quad'. If the |
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207 | type is 'fast', then this is equivalent to dtype 'single' with the |
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208 | fast flag set to True. |
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209 | """ |
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210 | # Assign default platform, overriding ocl with dll if OpenCL is unavailable |
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211 | if platform is None: |
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212 | platform = "ocl" |
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213 | if platform=="ocl" and not HAVE_OPENCL: |
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214 | platform = "dll" |
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215 | |
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216 | # Check if type indicates dll regardless of which platform is given |
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217 | if dtype is not None and dtype.endswith('!'): |
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218 | platform = "dll" |
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219 | dtype = dtype[:-1] |
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220 | |
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221 | # Convert special type names "half", "fast", and "quad" |
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222 | fast = (dtype=="fast") |
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223 | if fast: |
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224 | dtype = "single" |
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225 | elif dtype=="quad": |
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226 | dtype = "longdouble" |
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227 | elif dtype=="half": |
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228 | dtype = "f16" |
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229 | |
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230 | # Convert dtype string to numpy dtype. |
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231 | if dtype is None: |
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232 | numpy_dtype = generate.F32 if platform=="ocl" and model_info.single else generate.F64 |
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233 | else: |
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234 | numpy_dtype = np.dtype(dtype) |
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235 | |
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236 | # Make sure that the type is supported by opencl, otherwise use dll |
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237 | if platform=="ocl": |
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238 | env = kernelcl.environment() |
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239 | if not env.has_type(numpy_dtype): |
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240 | platform = "dll" |
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241 | if dtype is None: |
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242 | numpy_dtype = generate.F64 |
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243 | |
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244 | return numpy_dtype, fast, platform |
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245 | |
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246 | if __name__ == "__main__": |
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247 | import sys |
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248 | kind = sys.argv[1] if len(sys.argv) > 1 else "all" |
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249 | print("\n".join(list_models(kind))) |
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