| 1 | 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* @license\n * Copyright 2020 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport * as tf from '../index';\nimport {ALL_ENVS, describeWithFlags} from '../jasmine_util';\nimport {TypedArray} from '../types';\nimport {expectArrayInMeanStdRange} from './rand_util';\n\ndescribeWithFlags('truncatedNormal', ALL_ENVS, () => {\n // Expect slightly higher variances for truncated values.\n const EPSILON = 0.60;\n const SEED = 2002;\n\n function assertTruncatedValues(\n values: TypedArray, mean: number, stdv: number) {\n const bounds = mean + stdv * 2;\n for (let i = 0; i < values.length; i++) {\n expect(Math.abs(values[i])).toBeLessThanOrEqual(bounds);\n }\n }\n\n it('should return a random 1D float32 array', async () => {\n const shape: [number] = [1000];\n\n // Ensure defaults to float32 w/o type:\n let result = tf.truncatedNormal(shape, 0, 3.5, null, SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 3.5);\n expectArrayInMeanStdRange(await result.data(), 0, 3.5, EPSILON);\n\n result = tf.truncatedNormal(shape, 0, 4.5, 'float32', SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 4.5);\n expectArrayInMeanStdRange(await result.data(), 0, 4.5, EPSILON);\n });\n\n it('should return a randon 1D int32 array', async () => {\n const shape: [number] = [1000];\n const result = tf.truncatedNormal(shape, 0, 5, 'int32', SEED);\n expect(result.dtype).toBe('int32');\n assertTruncatedValues(await result.data(), 0, 5);\n expectArrayInMeanStdRange(await result.data(), 0, 5, EPSILON);\n });\n\n it('should return a 2D float32 array', async () => {\n const shape: [number, number] = [50, 50];\n\n // Ensure defaults to float32 w/o type:\n let result = tf.truncatedNormal(shape, 0, 3.5, null, SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 3.5);\n expectArrayInMeanStdRange(await result.data(), 0, 3.5, EPSILON);\n\n result = tf.truncatedNormal(shape, 0, 4.5, 'float32', SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 4.5);\n expectArrayInMeanStdRange(await result.data(), 0, 4.5, EPSILON);\n });\n\n it('should return a 2D int32 array', async () => {\n const shape: [number, number] = [50, 50];\n const result = tf.truncatedNormal(shape, 0, 5, 'int32', SEED);\n expect(result.dtype).toBe('int32');\n assertTruncatedValues(await result.data(), 0, 5);\n expectArrayInMeanStdRange(await result.data(), 0, 5, EPSILON);\n });\n\n it('should return a 3D float32 array', async () => {\n const shape: [number, number, number] = [10, 10, 10];\n\n // Ensure defaults to float32 w/o type:\n let result = tf.truncatedNormal(shape, 0, 3.5, null, SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 3.5);\n expectArrayInMeanStdRange(await result.data(), 0, 3.5, EPSILON);\n\n result = tf.truncatedNormal(shape, 0, 4.5, 'float32', SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 4.5);\n expectArrayInMeanStdRange(await result.data(), 0, 4.5, EPSILON);\n });\n\n it('should return a 3D int32 array', async () => {\n const shape: [number, number, number] = [10, 10, 10];\n const result = tf.truncatedNormal(shape, 0, 5, 'int32', SEED);\n expect(result.dtype).toBe('int32');\n assertTruncatedValues(await result.data(), 0, 5);\n expectArrayInMeanStdRange(await result.data(), 0, 5, EPSILON);\n });\n\n it('should return a 4D float32 array', async () => {\n const shape: [number, number, number, number] = [5, 5, 5, 5];\n\n // Ensure defaults to float32 w/o type:\n let result = tf.truncatedNormal(shape, 0, 3.5, null, SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 3.5);\n expectArrayInMeanStdRange(await result.data(), 0, 3.5, EPSILON);\n\n result = tf.truncatedNormal(shape, 0, 4.5, 'float32', SEED);\n expect(result.dtype).toBe('float32');\n assertTruncatedValues(await result.data(), 0, 4.5);\n expectArrayInMeanStdRange(await result.data(), 0, 4.5, EPSILON);\n });\n\n it('should return a 4D int32 array', async () => {\n const shape: [number, number, number, number] = [5, 5, 5, 5];\n const result = tf.truncatedNormal(shape, 0, 5, 'int32', SEED);\n expect(result.dtype).toBe('int32');\n assertTruncatedValues(await result.data(), 0, 5);\n expectArrayInMeanStdRange(await result.data(), 0, 5, EPSILON);\n });\n});\n"]} |