chore: import upstream snapshot with attribution

2026-07-13 12:47:05 +08:00
commit 4f3b7da785
7394 changed files with 2005594 additions and 0 deletions
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+/*
+ *  ******************************************************************************
+ *  *
+ *  *
+ *  * This program and the accompanying materials are made available under the
+ *  * terms of the Apache License, Version 2.0 which is available at
+ *  * https://www.apache.org/licenses/LICENSE-2.0.
+ *  *
+ *  * See the NOTICE file distributed with this work for additional
+ *  * information regarding copyright ownership.
+ *  * 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.
+ *  *
+ *  * SPDX-License-Identifier: Apache-2.0
+ *  *****************************************************************************
+ */
+
+//
+//  @author raver119@gmail.com
+//
+
+#ifndef LIBND4J_HEADERS_RANDOM_H
+#define LIBND4J_HEADERS_RANDOM_H
+#include <ops/declarable/headers/common.h>
+
+namespace sd {
+namespace ops {
+#if NOT_EXCLUDED(OP_set_seed)
+DECLARE_CUSTOM_OP(set_seed, -2, 1, false, 0, -2);
+#endif
+
+#if NOT_EXCLUDED(OP_get_seed)
+DECLARE_CUSTOM_OP(get_seed, -2, 1, false, 0, 0);
+#endif
+
+/*
+ * random_uniform distribution for types int32,int64, float16, float and double
+ * by default dtype is float32
+ *
+ * input:
+ *    0 - shape of output (1D int tensor)
+ *    1 - min val (0D of output type) - optional (0 as default)
+ *    2 - max val (0D of output type) - optional (inf as default)
+ *
+ * output:
+ *    0 - uniformly distributed values of given type (between min and max)
+ */
+#if NOT_EXCLUDED(OP_randomuniform)
+DECLARE_CUSTOM_OP(randomuniform, 1, 1, false, 0, -1);
+#endif
+/*
+ * multinomial (categorical) random generator draws samples from a multinomial distribution
+ *
+ * Input array:
+ *    0 - 2D ndarray with unnormalized log-probabilities with shape [batch_size (N), num_classes (K)]
+ *    1 - array with one int value of samples number, number of independent samples to draw for each experiment 1,N.
+ * Int arguments:
+ *    0 - optional argument, corresponds to dimension with batch_size
+ *    1 - optional argument, integer type to use for the output. Default int64.
+ *
+ * Output array:
+ *    0 - 2D ndarray with the drawn samples of shape [batch_size, num_samples]
+ */
+#if NOT_EXCLUDED(OP_random_multinomial)
+DECLARE_CUSTOM_OP(random_multinomial, 2, 1, false, 0, 0);
+#endif
+
+#if NOT_EXCLUDED(OP_random_normal)
+DECLARE_CUSTOM_OP(random_normal, 1, 1, true, 2, 0);
+#endif
+
+#if NOT_EXCLUDED(OP_random_bernoulli)
+DECLARE_CUSTOM_OP(random_bernoulli, 1, 1, true, 0, 1);
+#endif
+
+#if NOT_EXCLUDED(OP_random_exponential)
+DECLARE_CUSTOM_OP(random_exponential, 1, 1, true, 1, 0);
+#endif
+
+#if NOT_EXCLUDED(OP_random_crop)
+DECLARE_CUSTOM_OP(random_crop, 2, 1, false, 0, 0);
+#endif
+
+/**
+ * random_gamma op.
+ */
+#if NOT_EXCLUDED(OP_random_gamma)
+DECLARE_CUSTOM_OP(random_gamma, 2, 1, false, 0, 0);
+#endif
+
+/**
+ * random_poisson op.
+ */
+#if NOT_EXCLUDED(OP_random_poisson)
+DECLARE_CUSTOM_OP(random_poisson, 2, 1, false, 0, 0);
+#endif
+
+}  // namespace ops
+}  // namespace sd
+
+#endif