"use strict"; /** * @license * Copyright 2018 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ Object.defineProperty(exports, "__esModule", { value: true }); var util_1 = require("./util"); // Maximum number of values before we decide to show ellipsis. var FORMAT_LIMIT_NUM_VALS = 20; // Number of first and last values to show when displaying a, b,...,y, z. var FORMAT_NUM_FIRST_LAST_VALS = 3; // Number of significant digits to show. var FORMAT_NUM_SIG_DIGITS = 7; function tensorToString(vals, shape, dtype, verbose) { var strides = util_1.computeStrides(shape); var padPerCol = computeMaxSizePerColumn(vals, shape, dtype, strides); var rank = shape.length; var valsLines = subTensorToString(vals, shape, dtype, strides, padPerCol); var lines = ['Tensor']; if (verbose) { lines.push(" dtype: " + dtype); lines.push(" rank: " + rank); lines.push(" shape: [" + shape + "]"); lines.push(" values:"); } lines.push(valsLines.map(function (l) { return ' ' + l; }).join('\n')); return lines.join('\n'); } exports.tensorToString = tensorToString; function computeMaxSizePerColumn(vals, shape, dtype, strides) { var n = util_1.sizeFromShape(shape); var numCols = strides[strides.length - 1]; var padPerCol = new Array(numCols).fill(0); var rank = shape.length; var valuesOrTuples = dtype === 'complex64' ? createComplexTuples(vals) : vals; if (rank > 1) { for (var row = 0; row < n / numCols; row++) { var offset = row * numCols; for (var j = 0; j < numCols; j++) { padPerCol[j] = Math.max(padPerCol[j], valToString(valuesOrTuples[offset + j], 0, dtype).length); } } } return padPerCol; } function valToString(val, pad, dtype) { var valStr; if (Array.isArray(val)) { valStr = parseFloat(val[0].toFixed(FORMAT_NUM_SIG_DIGITS)) + " + " + (parseFloat(val[1].toFixed(FORMAT_NUM_SIG_DIGITS)) + "j"); } else if (util_1.isString(val)) { valStr = "'" + val + "'"; } else if (dtype === 'bool') { valStr = boolNumToString(val); } else { valStr = parseFloat(val.toFixed(FORMAT_NUM_SIG_DIGITS)).toString(); } return util_1.rightPad(valStr, pad); } function boolNumToString(v) { return v === 0 ? 'false' : 'true'; } function subTensorToString(vals, shape, dtype, strides, padPerCol, isLast) { if (isLast === void 0) { isLast = true; } var storagePerElement = dtype === 'complex64' ? 2 : 1; var size = shape[0]; var rank = shape.length; if (rank === 0) { if (dtype === 'complex64') { var complexTuple = createComplexTuples(vals); return [valToString(complexTuple[0], 0, dtype)]; } if (dtype === 'bool') { return [boolNumToString(vals[0])]; } return [vals[0].toString()]; } if (rank === 1) { if (size > FORMAT_LIMIT_NUM_VALS) { var firstValsSize = FORMAT_NUM_FIRST_LAST_VALS * storagePerElement; var firstVals = Array.from(vals.slice(0, firstValsSize)); var lastVals = Array.from(vals.slice((size - FORMAT_NUM_FIRST_LAST_VALS) * storagePerElement, size * storagePerElement)); if (dtype === 'complex64') { firstVals = createComplexTuples(firstVals); lastVals = createComplexTuples(lastVals); } return [ '[' + firstVals.map(function (x, i) { return valToString(x, padPerCol[i], dtype); }) .join(', ') + ', ..., ' + lastVals .map(function (x, i) { return valToString(x, padPerCol[size - FORMAT_NUM_FIRST_LAST_VALS + i], dtype); }) .join(', ') + ']' ]; } var displayVals = dtype === 'complex64' ? createComplexTuples(vals) : Array.from(vals); return [ '[' + displayVals.map(function (x, i) { return valToString(x, padPerCol[i], dtype); }) .join(', ') + ']' ]; } // The array is rank 2 or more. var subshape = shape.slice(1); var substrides = strides.slice(1); var stride = strides[0] * storagePerElement; var lines = []; if (size > FORMAT_LIMIT_NUM_VALS) { for (var i = 0; i < FORMAT_NUM_FIRST_LAST_VALS; i++) { var start = i * stride; var end = start + stride; lines.push.apply(lines, subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, false /* isLast */)); } lines.push('...'); for (var i = size - FORMAT_NUM_FIRST_LAST_VALS; i < size; i++) { var start = i * stride; var end = start + stride; lines.push.apply(lines, subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, i === size - 1 /* isLast */)); } } else { for (var i = 0; i < size; i++) { var start = i * stride; var end = start + stride; lines.push.apply(lines, subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, i === size - 1 /* isLast */)); } } var sep = rank === 2 ? ',' : ''; lines[0] = '[' + lines[0] + sep; for (var i = 1; i < lines.length - 1; i++) { lines[i] = ' ' + lines[i] + sep; } var newLineSep = ',\n'; for (var i = 2; i < rank; i++) { newLineSep += '\n'; } lines[lines.length - 1] = ' ' + lines[lines.length - 1] + ']' + (isLast ? '' : newLineSep); return lines; } function createComplexTuples(vals) { var complexTuples = []; for (var i = 0; i < vals.length; i += 2) { complexTuples.push([vals[i], vals[i + 1]]); } return complexTuples; } //# sourceMappingURL=tensor_format.js.map