This sampler supports broadcasting of its input parameters as well as puts the # samples at the left of the output shape, rather than the right. PiperOrigin-RevId: 317129622 Change-Id: I4b62ad2e89a9637ae8b30b73af4b662ad0caa943
124 lines
5.8 KiB
Plaintext
124 lines
5.8 KiB
Plaintext
path: "tensorflow.random"
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tf_module {
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member {
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name: "Algorithm"
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mtype: "<class \'enum.EnumMeta\'>"
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}
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member {
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name: "Generator"
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mtype: "<type \'type\'>"
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}
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member {
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name: "experimental"
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mtype: "<type \'module\'>"
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}
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member_method {
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name: "all_candidate_sampler"
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argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
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}
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member_method {
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name: "categorical"
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argspec: "args=[\'logits\', \'num_samples\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
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}
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member_method {
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name: "create_rng_state"
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argspec: "args=[\'seed\', \'alg\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "fixed_unigram_candidate_sampler"
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argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'vocab_file\', \'distortion\', \'num_reserved_ids\', \'num_shards\', \'shard\', \'unigrams\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'1.0\', \'0\', \'1\', \'0\', \'()\', \'None\', \'None\'], "
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}
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member_method {
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name: "gamma"
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argspec: "args=[\'shape\', \'alpha\', \'beta\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
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}
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member_method {
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name: "get_global_generator"
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argspec: "args=[], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_seed"
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argspec: "args=[\'op_seed\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "learned_unigram_candidate_sampler"
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argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
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}
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member_method {
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name: "log_uniform_candidate_sampler"
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argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
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}
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member_method {
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name: "multinomial"
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argspec: "args=[\'logits\', \'num_samples\', \'seed\', \'name\', \'output_dtype\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
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}
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member_method {
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name: "normal"
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argspec: "args=[\'shape\', \'mean\', \'stddev\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
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}
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member_method {
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name: "poisson"
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argspec: "args=[\'lam\', \'shape\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\", \'None\', \'None\'], "
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}
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member_method {
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name: "set_global_generator"
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argspec: "args=[\'generator\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "set_random_seed"
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argspec: "args=[\'seed\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "shuffle"
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argspec: "args=[\'value\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
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}
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member_method {
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name: "stateless_binomial"
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argspec: "args=[\'shape\', \'seed\', \'counts\', \'probs\', \'output_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
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}
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member_method {
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name: "stateless_categorical"
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argspec: "args=[\'logits\', \'num_samples\', \'seed\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int64\'>\", \'None\'], "
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}
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member_method {
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name: "stateless_gamma"
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argspec: "args=[\'shape\', \'seed\', \'alpha\', \'beta\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'float32\'>\", \'None\'], "
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}
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member_method {
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name: "stateless_multinomial"
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argspec: "args=[\'logits\', \'num_samples\', \'seed\', \'output_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int64\'>\", \'None\'], "
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}
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member_method {
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name: "stateless_normal"
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argspec: "args=[\'shape\', \'seed\', \'mean\', \'stddev\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \"<dtype: \'float32\'>\", \'None\'], "
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}
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member_method {
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name: "stateless_parameterized_truncated_normal"
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argspec: "args=[\'shape\', \'seed\', \'means\', \'stddevs\', \'minvals\', \'maxvals\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \'-2.0\', \'2.0\', \'None\'], "
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}
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member_method {
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name: "stateless_poisson"
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argspec: "args=[\'shape\', \'seed\', \'lam\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
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}
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member_method {
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name: "stateless_truncated_normal"
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argspec: "args=[\'shape\', \'seed\', \'mean\', \'stddev\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \"<dtype: \'float32\'>\", \'None\'], "
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}
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member_method {
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name: "stateless_uniform"
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argspec: "args=[\'shape\', \'seed\', \'minval\', \'maxval\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'None\', \"<dtype: \'float32\'>\", \'None\'], "
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}
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member_method {
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name: "truncated_normal"
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argspec: "args=[\'shape\', \'mean\', \'stddev\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
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}
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member_method {
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name: "uniform"
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argspec: "args=[\'shape\', \'minval\', \'maxval\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'None\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
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}
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member_method {
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name: "uniform_candidate_sampler"
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argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
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}
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}
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