|
| 1 | +# Data Parallel Control (dpctl) |
| 2 | +# |
| 3 | +# Copyright 2020-2022 Intel Corporation |
| 4 | +# |
| 5 | +# Licensed under the Apache License, Version 2.0 (the "License"); |
| 6 | +# you may not use this file except in compliance with the License. |
| 7 | +# You may obtain a copy of the License at |
| 8 | +# |
| 9 | +# http://www.apache.org/licenses/LICENSE-2.0 |
| 10 | +# |
| 11 | +# Unless required by applicable law or agreed to in writing, software |
| 12 | +# distributed under the License is distributed on an "AS IS" BASIS, |
| 13 | +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 14 | +# See the License for the specific language governing permissions and |
| 15 | +# limitations under the License. |
| 16 | + |
| 17 | +import contextlib |
| 18 | +import operator |
| 19 | + |
| 20 | +import numpy as np |
| 21 | + |
| 22 | +import dpctl.tensor as dpt |
| 23 | + |
| 24 | +__doc__ = "Print functions for :class:`dpctl.tensor.usm_ndarray`." |
| 25 | + |
| 26 | +_print_options = { |
| 27 | + "linewidth": 75, |
| 28 | + "edgeitems": 3, |
| 29 | + "threshold": 1000, |
| 30 | + "precision": 8, |
| 31 | + "floatmode": "maxprec", |
| 32 | + "suppress": False, |
| 33 | + "nanstr": "nan", |
| 34 | + "infstr": "inf", |
| 35 | + "sign": "-", |
| 36 | +} |
| 37 | + |
| 38 | + |
| 39 | +def _options_dict( |
| 40 | + linewidth=None, |
| 41 | + edgeitems=None, |
| 42 | + threshold=None, |
| 43 | + precision=None, |
| 44 | + floatmode=None, |
| 45 | + suppress=None, |
| 46 | + nanstr=None, |
| 47 | + infstr=None, |
| 48 | + sign=None, |
| 49 | + numpy=False, |
| 50 | +): |
| 51 | + if numpy: |
| 52 | + numpy_options = np.get_printoptions() |
| 53 | + options = {k: numpy_options[k] for k in _print_options.keys()} |
| 54 | + else: |
| 55 | + options = _print_options.copy() |
| 56 | + |
| 57 | + if suppress: |
| 58 | + options["suppress"] = True |
| 59 | + |
| 60 | + local = dict(locals().items()) |
| 61 | + for int_arg in ["linewidth", "precision", "threshold", "edgeitems"]: |
| 62 | + val = local[int_arg] |
| 63 | + if val is not None: |
| 64 | + options[int_arg] = operator.index(val) |
| 65 | + |
| 66 | + for str_arg in ["nanstr", "infstr"]: |
| 67 | + val = local[str_arg] |
| 68 | + if val is not None: |
| 69 | + if not isinstance(val, str): |
| 70 | + raise TypeError( |
| 71 | + "`{}` ".format(str_arg) + "must be of `string` type." |
| 72 | + ) |
| 73 | + options[str_arg] = val |
| 74 | + |
| 75 | + signs = ["-", "+", " "] |
| 76 | + if sign is not None: |
| 77 | + if sign not in signs: |
| 78 | + raise ValueError( |
| 79 | + "`sign` must be one of" |
| 80 | + + ", ".join("`{}`".format(s) for s in signs) |
| 81 | + ) |
| 82 | + options["sign"] = sign |
| 83 | + |
| 84 | + floatmodes = ["fixed", "unique", "maxprec", "maxprec_equal"] |
| 85 | + if floatmode is not None: |
| 86 | + if floatmode not in floatmodes: |
| 87 | + raise ValueError( |
| 88 | + "`floatmode` must be one of" |
| 89 | + + ", ".join("`{}`".format(m) for m in floatmodes) |
| 90 | + ) |
| 91 | + options["floatmode"] = floatmode |
| 92 | + |
| 93 | + return options |
| 94 | + |
| 95 | + |
| 96 | +def set_print_options( |
| 97 | + linewidth=None, |
| 98 | + edgeitems=None, |
| 99 | + threshold=None, |
| 100 | + precision=None, |
| 101 | + floatmode=None, |
| 102 | + suppress=None, |
| 103 | + nanstr=None, |
| 104 | + infstr=None, |
| 105 | + sign=None, |
| 106 | + numpy=False, |
| 107 | +): |
| 108 | + """ |
| 109 | + set_print_options(linewidth=None, edgeitems=None, threshold=None, |
| 110 | + precision=None, floatmode=None, suppress=None, nanstr=None, |
| 111 | + infstr=None, sign=None, numpy=False) |
| 112 | +
|
| 113 | + Set options for printing ``dpctl.tensor.usm_ndarray`` class. |
| 114 | +
|
| 115 | + Args: |
| 116 | + linewidth (int, optional): Number of characters printed per line. |
| 117 | + Raises `TypeError` if linewidth is not an integer. |
| 118 | + Default: `75`. |
| 119 | + edgeitems (int, optional): Number of elements at the beginning and end |
| 120 | + when the printed array is abbreviated. |
| 121 | + Raises `TypeError` if edgeitems is not an integer. |
| 122 | + Default: `3`. |
| 123 | + threshold (int, optional): Number of elements that triggers array |
| 124 | + abbreviation. |
| 125 | + Raises `TypeError` if threshold is not an integer. |
| 126 | + Default: `1000`. |
| 127 | + precision (int or None, optional): Number of digits printed for |
| 128 | + floating point numbers. |
| 129 | + Raises `TypeError` if precision is not an integer. |
| 130 | + Default: `8`. |
| 131 | + floatmode (str, optional): Controls how floating point |
| 132 | + numbers are interpreted. |
| 133 | +
|
| 134 | + `"fixed:`: Always prints exactly `precision` digits. |
| 135 | + `"unique"`: Ignores precision, prints the number of |
| 136 | + digits necessary to uniquely specify each number. |
| 137 | + `"maxprec"`: Prints `precision` digits or fewer, |
| 138 | + if fewer will uniquely represent a number. |
| 139 | + `"maxprec_equal"`: Prints an equal number of digits |
| 140 | + for each number. This number is `precision` digits or fewer, |
| 141 | + if fewer will uniquely represent each number. |
| 142 | + Raises `ValueError` if floatmode is not one of |
| 143 | + `fixed`, `unique`, `maxprec`, or `maxprec_equal`. |
| 144 | + Default: "maxprec_equal" |
| 145 | + suppress (bool, optional): If `True,` numbers equal to zero |
| 146 | + in the current precision will print as zero. |
| 147 | + Default: `False`. |
| 148 | + nanstr (str, optional): String used to repesent nan. |
| 149 | + Raises `TypeError` if nanstr is not a string. |
| 150 | + Default: `"nan"`. |
| 151 | + infstr (str, optional): String used to represent infinity. |
| 152 | + Raises `TypeError` if infstr is not a string. |
| 153 | + Default: `"inf"`. |
| 154 | + sign (str, optional): Controls the sign of floating point |
| 155 | + numbers. |
| 156 | + `"-"`: Omit the sign of positive numbers. |
| 157 | + `"+"`: Always print the sign of positive numbers. |
| 158 | + `" "`: Always print a whitespace in place of the |
| 159 | + sign of positive numbers. |
| 160 | + Raises `ValueError` if sign is not one of |
| 161 | + `"-"`, `"+"`, or `" "`. |
| 162 | + Default: `"-"`. |
| 163 | + numpy (bool, optional): If `True,` then before other specified print |
| 164 | + options are set, a dictionary of Numpy's print options |
| 165 | + will be used to initialize dpctl's print options. |
| 166 | + Default: "False" |
| 167 | + """ |
| 168 | + options = _options_dict( |
| 169 | + linewidth=linewidth, |
| 170 | + edgeitems=edgeitems, |
| 171 | + threshold=threshold, |
| 172 | + precision=precision, |
| 173 | + floatmode=floatmode, |
| 174 | + suppress=suppress, |
| 175 | + nanstr=nanstr, |
| 176 | + infstr=infstr, |
| 177 | + sign=sign, |
| 178 | + numpy=numpy, |
| 179 | + ) |
| 180 | + _print_options.update(options) |
| 181 | + |
| 182 | + |
| 183 | +def get_print_options(): |
| 184 | + """ |
| 185 | + get_print_options() -> dict |
| 186 | +
|
| 187 | + Returns a copy of current options for printing |
| 188 | + ``dpctl.tensor.usm_ndarray`` class. |
| 189 | +
|
| 190 | + Options: |
| 191 | + - "linewidth" : int, default 75 |
| 192 | + - "edgeitems" : int, default 3 |
| 193 | + - "threshold" : int, default 1000 |
| 194 | + - "precision" : int, default 8 |
| 195 | + - "floatmode" : str, default "maxprec_equal" |
| 196 | + - "suppress" : bool, default False |
| 197 | + - "nanstr" : str, default "nan" |
| 198 | + - "infstr" : str, default "inf" |
| 199 | + - "sign" : str, default "-" |
| 200 | + """ |
| 201 | + return _print_options.copy() |
| 202 | + |
| 203 | + |
| 204 | +@contextlib.contextmanager |
| 205 | +def print_options(*args, **kwargs): |
| 206 | + """ |
| 207 | + Context manager for print options. |
| 208 | +
|
| 209 | + Set print options for the scope of a `with` block. |
| 210 | + `as` yields dictionary of print options. |
| 211 | + """ |
| 212 | + options = dpt.get_print_options() |
| 213 | + try: |
| 214 | + dpt.set_print_options(*args, **kwargs) |
| 215 | + yield dpt.get_print_options() |
| 216 | + finally: |
| 217 | + dpt.set_print_options(**options) |
| 218 | + |
| 219 | + |
| 220 | +def _nd_corners(x, edge_items, slices=()): |
| 221 | + axes_reduced = len(slices) |
| 222 | + if axes_reduced == x.ndim: |
| 223 | + return x[slices] |
| 224 | + |
| 225 | + if x.shape[axes_reduced] > 2 * edge_items: |
| 226 | + return dpt.concat( |
| 227 | + ( |
| 228 | + _nd_corners( |
| 229 | + x, edge_items, slices + (slice(None, edge_items, None),) |
| 230 | + ), |
| 231 | + _nd_corners( |
| 232 | + x, edge_items, slices + (slice(-edge_items, None, None),) |
| 233 | + ), |
| 234 | + ), |
| 235 | + axis=axes_reduced, |
| 236 | + ) |
| 237 | + else: |
| 238 | + return _nd_corners(x, edge_items, slices + (slice(None, None, None),)) |
| 239 | + |
| 240 | + |
| 241 | +def _usm_ndarray_str( |
| 242 | + x, |
| 243 | + line_width=None, |
| 244 | + edge_items=None, |
| 245 | + threshold=None, |
| 246 | + precision=None, |
| 247 | + floatmode=None, |
| 248 | + suppress=None, |
| 249 | + sign=None, |
| 250 | + numpy=False, |
| 251 | + separator=" ", |
| 252 | + prefix="", |
| 253 | + suffix="", |
| 254 | +): |
| 255 | + if not isinstance(x, dpt.usm_ndarray): |
| 256 | + raise TypeError(f"Expected dpctl.tensor.usm_ndarray, got {type(x)}") |
| 257 | + |
| 258 | + options = get_print_options() |
| 259 | + options.update( |
| 260 | + _options_dict( |
| 261 | + linewidth=line_width, |
| 262 | + edgeitems=edge_items, |
| 263 | + threshold=threshold, |
| 264 | + precision=precision, |
| 265 | + floatmode=floatmode, |
| 266 | + suppress=suppress, |
| 267 | + sign=sign, |
| 268 | + numpy=numpy, |
| 269 | + ) |
| 270 | + ) |
| 271 | + |
| 272 | + threshold = options["threshold"] |
| 273 | + edge_items = options["edgeitems"] |
| 274 | + |
| 275 | + if x.size > threshold: |
| 276 | + # need edge_items + 1 elements for np.array2string to abbreviate |
| 277 | + data = dpt.asnumpy(_nd_corners(x, edge_items + 1)) |
| 278 | + options["threshold"] = 0 |
| 279 | + else: |
| 280 | + data = dpt.asnumpy(x) |
| 281 | + with np.printoptions(**options): |
| 282 | + s = np.array2string( |
| 283 | + data, separator=separator, prefix=prefix, suffix=suffix |
| 284 | + ) |
| 285 | + return s |
| 286 | + |
| 287 | + |
| 288 | +def _usm_ndarray_repr(x, line_width=None, precision=None, suppress=None): |
| 289 | + if not isinstance(x, dpt.usm_ndarray): |
| 290 | + raise TypeError(f"Expected dpctl.tensor.usm_ndarray, got {type(x)}") |
| 291 | + |
| 292 | + if line_width is None: |
| 293 | + line_width = _print_options["linewidth"] |
| 294 | + |
| 295 | + show_dtype = x.dtype not in [ |
| 296 | + dpt.bool, |
| 297 | + dpt.int64, |
| 298 | + dpt.float64, |
| 299 | + dpt.complex128, |
| 300 | + ] |
| 301 | + |
| 302 | + prefix = "usm_ndarray(" |
| 303 | + suffix = ")" |
| 304 | + |
| 305 | + s = _usm_ndarray_str( |
| 306 | + x, |
| 307 | + line_width=line_width, |
| 308 | + precision=precision, |
| 309 | + suppress=suppress, |
| 310 | + separator=", ", |
| 311 | + prefix=prefix, |
| 312 | + suffix=suffix, |
| 313 | + ) |
| 314 | + |
| 315 | + if show_dtype: |
| 316 | + dtype_str = "dtype={}".format(x.dtype.name) |
| 317 | + bottom_len = len(s) - (s.rfind("\n") + 1) |
| 318 | + next_line = bottom_len + len(dtype_str) + 1 > line_width |
| 319 | + dtype_str = ",\n" + dtype_str if next_line else ", " + dtype_str |
| 320 | + else: |
| 321 | + dtype_str = "" |
| 322 | + |
| 323 | + return prefix + s + dtype_str + suffix |
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