Re-exports§
pub use crate::std::attention_std::AttentionStdError as AttentionError;pub use crate::std::attention_std::scaled_dot_product_attention;pub use crate::std::attention_std::AttentionStdError;pub use crate::std::batching_std::BatchStdError as BatchError;pub use crate::std::batching_std::count_non_pad as batching_count_non_pad;pub use crate::std::batching_std::for_each_token_row as batching_for_each_token_row;pub use crate::std::batching_std::make_padding_mask as batching_make_padding_mask;pub use crate::std::batching_std::max_sequence_len as batching_max_sequence_len;pub use crate::std::batching_std::pad_sequences_u32 as batching_pad_sequences_u32;pub use crate::std::batching_std::sequence_lengths as batching_sequence_lengths;pub use crate::std::batching_std::BatchStdError;pub use crate::std::beam_search_std::BeamStdError as BeamError;pub use crate::std::beam_search_std::log_softmax_in_place as beam_log_soft_max_in_place;pub use crate::std::beam_search_std::prune_by_threshold as beam_prune_by_threshold;pub use crate::std::beam_search_std::select_top_beams as beam_select_top_beams;pub use crate::std::beam_search_std::BeamStdError;pub use crate::std::conv3d_std::conv3d_forward;pub use crate::std::conv3d_std::conv3d_is_compatible as conv3d_layout_compatible;pub use crate::std::conv3d_std::conv3d_forward as conv3d_forward_std;pub use crate::std::conv3d_std::conv3d_is_compatible;pub use crate::std::conv3d_std::conv3d_output_shape as conv3d_output_shape_std;pub use crate::std::conv5d_std::conv5d_forward;pub use crate::std::conv5d_std::conv5d_backward as conv5d_backward_std;pub use crate::std::conv5d_std::conv5d_forward as conv5d_forward_std;pub use crate::std::conv5d_std::conv5d_output_shape as conv5d_output_shape_std;pub use crate::std::crypto_std::Sha256Std as Sha256Ctx;pub use crate::std::crypto_std::Sha512Std as Sha512Ctx;pub use crate::std::crypto_std::constant_time_eq;pub use crate::std::crypto_std::digest_to_hex_lower;pub use crate::std::crypto_std::verify_sha256;pub use crate::std::crypto_std::verify_sha512;pub use crate::std::crypto_std::sha256_bytes;pub use crate::std::crypto_std::sha512_bytes;pub use crate::std::crypto_std::Sha256Std;pub use crate::std::crypto_std::Sha512Std;pub use crate::std::embeddings_std::tied_output_projection;pub use crate::std::embeddings_std::EmbeddingsStdError as EmbeddingError;pub use crate::std::embeddings_std::gather_embeddings;pub use crate::std::embeddings_std::EmbeddingsStdError;pub use crate::std::engine_std::forward_dense_plan_big_kernel;pub use crate::std::engine_std::forward_plan as forward_dense_plan;pub use crate::std::engine_std::forward_plan as forward_dense_plan_std;pub use crate::std::engine_std::EngineStdError as ForwardError;pub use crate::std::engine_std::forward_batch_big_kernel;pub use crate::std::engine_std::forward_plan;pub use crate::std::engine_std::required_batch_scratch_len;pub use crate::std::engine_std::EngineStdError;pub use crate::std::engine_std::required_single_infer_scratch;pub use crate::std::engine_std::validate_forward_io;pub use crate::std::gradients_std::GradientStdError as GradientError;pub use crate::std::gradients_std::all_finite as gradients_all_finite;pub use crate::std::gradients_std::clip_by_global_norm as gradients_clip_by_global_norm;pub use crate::std::gradients_std::has_inf as gradients_has_inf;pub use crate::std::gradients_std::has_nan as gradients_has_nan;pub use crate::std::gradients_std::l2_norm as gradients_l2_norm;pub use crate::std::gradients_std::within_abs_bound as gradients_within_abs_bound;pub use crate::std::gradients_std::GradientStdError;pub use crate::std::inference_std::softmax as softmax_stable;pub use crate::std::inference_std::InferenceStdError as InferenceError;pub use crate::std::inference_std::argmax_index;pub use crate::std::inference_std::normalize_logits_in_place;pub use crate::std::inference_std::forward_dense_batch;pub use crate::std::inference_std::softmax;pub use crate::std::inference_std::InferenceStdError;pub use crate::std::initializers_std::expected_parameter_counts;pub use crate::std::initializers_std::initialize_dense_parameters;pub use crate::std::kv_cache_std::KvCacheError;pub use crate::std::kv_cache_std::KvCacheStd;pub use crate::std::kv_cache_std::KvCacheViewStd;pub use crate::std::kv_cache_std::KvCacheViewStd as KvCacheView;pub use crate::std::layers_std::DenseLayerDesc;pub use crate::std::layers_std::LayerStdError as LayerError;pub use crate::std::layers_std::build_dense_specs_from_layers as build_dense_specs_from_layers_std;pub use crate::std::layers_std::LayerStdError;pub use crate::std::lora_std::LoraStdError as LoraError;pub use crate::std::lora_std::apply_lora_delta;pub use crate::std::lora_std::LoraStdError;pub use crate::std::losses_std::LossKindStd as LossKind;pub use crate::std::losses_std::LossesStdError as LossError;pub use crate::std::losses_std::loss_and_gradient;pub use crate::std::losses_std::reduce_mean;pub use crate::std::losses_std::reduce_sum;pub use crate::std::losses_std::LossesStdError;pub use crate::std::metrics_std::MetricsStdError as MetricError;pub use crate::std::metrics_std::RunningMeanStd;pub use crate::std::metrics_std::RunningMeanStd as RunningMean;pub use crate::std::metrics_std::accuracy_top1_from_one_hot;pub use crate::std::metrics_std::argmax;pub use crate::std::metrics_std::cross_entropy_from_probabilities;pub use crate::std::metrics_std::mae;pub use crate::std::metrics_std::mse;pub use crate::std::metrics_std::MetricsStdError;pub use crate::std::model_config_std::ModelConfigStdError as ConfigError;pub use crate::std::model_config_std::approximate_parameter_count;pub use crate::std::model_config_std::attention_head_dim;pub use crate::std::model_config_std::validate as validate_config;pub use crate::std::model_config_std::ModelConfigStdError;pub use crate::std::model_config_std::base_transformer;pub use crate::std::model_config_std::small_transformer;pub use crate::std::model_config_std::tiny_transformer;pub use crate::std::model_format_std::DecodedCountsStd as DecodedCounts;pub use crate::std::model_format_std::LayerSpec;pub use crate::std::model_format_std::ModelFormatStdError as ModelFormatError;pub use crate::std::model_format_std::decode_dense_model;pub use crate::std::model_format_std::encode_dense_model;pub use crate::std::model_format_std::encoded_size;pub use crate::std::model_format_std::ModelFormatStdError;pub use crate::std::model_format_std::decode_dense_model_v1;pub use crate::std::model_format_std::encode_dense_model_v1;pub use crate::std::model_format_std::encoded_size_v1;pub use crate::std::model_format_std::DecodedCountsStd;pub use crate::std::model_std::ModelStd;pub use crate::std::moe_std::MoeStdError as MoeError;pub use crate::std::moe_std::route_top1 as moe_route_top1;pub use crate::std::moe_std::top1_gating as moe_top1_gating;pub use crate::std::moe_std::MoeStdError;pub use crate::std::network_std::NetworkStatsStd as NetworkStats;pub use crate::std::network_std::NeuralNetworkStd as NetworkStd_NeuralNetworkStd;pub use crate::std::network_std::network_stats as network_stats_from_parts;pub use crate::std::network_std::validate_network_parts;pub use crate::std::network_std::NetworkStatsStd;pub use crate::std::neural_network_std::NeuralNetworkStd;pub use crate::std::neural_network_std::NeuralNetworkStd as NeuralNetwork;pub use crate::std::normalization_std::NormStdError as NormError;pub use crate::std::normalization_std::layer_norm;pub use crate::std::normalization_std::layer_norm_in_place;pub use crate::std::normalization_std::NormStdError;pub use crate::std::normalization_std::rms_norm;pub use crate::std::normalization_std::rms_norm_in_place;pub use crate::std::optimizers_std::apply_optimizer_step;pub use crate::std::optimizers_std::optimizer_state_len;pub use crate::std::optimizers_std::OptimizerKind;pub use crate::std::optimizers_std::OptimizerStdError as OptimizerError;pub use crate::std::profiler_std::arithmetic_intensity as profiler_arithmetic_intensity;pub use crate::std::profiler_std::bytes_per_second as profiler_bytes_per_second;pub use crate::std::profiler_std::has_recorded_work as profiler_has_recorded_work;pub use crate::std::profiler_std::is_memory_heavy as profiler_is_memory_heavy;pub use crate::std::profiler_std::opcounter_new;pub use crate::std::profiler_std::ops_per_second as profiler_ops_per_second;pub use crate::std::quantization_std::QuantizationStdError as QuantError;pub use crate::std::quantization_std::dequantize_i8_symmetric;pub use crate::std::quantization_std::matmul_i8_f32;pub use crate::std::quantization_std::quantize_i8_symmetric;pub use crate::std::quantization_std::QuantizationStdError;pub use crate::std::rnn_std::parse_rnn_from_bytes as parse_rnn_from_bytes_std;pub use crate::std::rnn_std::parse_rnn_from_bytes;pub use crate::std::rnn_std::BlobMetaStd as BlobMeta;pub use crate::std::rnn_std::RnnStd as RnnHandle;pub use crate::std::rnn_std::RnnStdError as RnnApiError;pub use crate::std::rnn_std::BlobMetaStd;pub use crate::std::rnn_std::RnnStd;pub use crate::std::rnn_std::RnnStdError;pub use crate::std::rope_std::RopeStdError as RopeError;pub use crate::std::rope_std::apply_rope_in_place;pub use crate::std::rope_std::RopeStdError;pub use crate::std::runtime_std::RuntimeStdError as RuntimeError;pub use crate::std::runtime_std::check_runtime_budget;pub use crate::std::runtime_std::estimate_runtime_flops;pub use crate::std::runtime_std::estimate_runtime_memory;pub use crate::std::runtime_std::estimate_tokens_per_second;pub use crate::std::runtime_std::fit_from_estimate;pub use crate::std::runtime_std::BudgetFit;pub use crate::std::runtime_std::RuntimeEstimate;pub use crate::std::runtime_std::RuntimeFlopsEstimate;pub use crate::std::runtime_std::RuntimeStdError;pub use crate::std::runtime_std::ThroughputEstimate;pub use crate::std::sampling_std::SamplingStdError as SamplingError;pub use crate::std::sampling_std::argmax_sample;pub use crate::std::sampling_std::sample_from_cumulative;pub use crate::std::sampling_std::softmax_temperature;pub use crate::std::sampling_std::top_k_mask;pub use crate::std::sampling_std::top_p_cutoff;pub use crate::std::sampling_std::SamplingStdError;pub use crate::std::schedulers_std::LrScheduleStd as LrSchedule;pub use crate::std::schedulers_std::ScheduleStdError as ScheduleError;pub use crate::std::schedulers_std::compute_learning_rate;pub use crate::std::schedulers_std::LrScheduleStd;pub use crate::std::schedulers_std::ScheduleStdError;pub use crate::std::scratch_std::ScratchStd;pub use crate::std::scratch_std::ScratchStd as Scratch;pub use crate::std::sphere5d_std::Sphere5DStd as Sphere5D;pub use crate::std::sphere5d_std::SphereStdError as SphereError;pub use crate::std::sphere5d_std::Sphere5DStd;pub use crate::std::sphere5d_std::SphereStdError;pub use crate::std::tensor_std::tensor_add_in_place;pub use crate::std::tensor_std::tensor_fill as tensor_fill_std;pub use crate::std::tensor_std::tensor_fill;pub use crate::std::tensor_std::tensor_scale_in_place;pub use crate::std::tensor_std::TensorStd;pub use crate::std::tensor_std::TensorStd as TensorViewStd;pub use crate::std::tensor_std::TensorStd as TensorView;pub use crate::std::trainer_std::TrainerStdError as TrainError;pub use crate::std::trainer_std::dense_sgd_step;pub use crate::std::trainer_std::required_train_buffer_len;pub use crate::std::trainer_std::TrainerStdError;pub use crate::std::visualization_std::get_network_from_rnn;