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pytensor_ml

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  • Installation
  • 🔪 Sharp Edges 🔪
  • Example Gallery
  • API Reference
  • Developer Guide
  • GitHub

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  • Model
    • pytensor_ml.model.Model
      • pytensor_ml.model.Model.__init__
      • pytensor_ml.model.Model.compile_train
      • pytensor_ml.model.Model.initialize
      • pytensor_ml.model.Model.predict
  • Layers
    • pytensor_ml.layers.Layer
    • pytensor_ml.layers.Input
    • pytensor_ml.layers.Sequential
    • pytensor_ml.layers.Concatenate
    • pytensor_ml.layers.Flatten
    • pytensor_ml.layers.Squeeze
    • pytensor_ml.layers.Linear
      • pytensor_ml.layers.Linear.__init__
    • pytensor_ml.layers.Embedding
      • pytensor_ml.layers.Embedding.__init__
    • pytensor_ml.layers.Conv1D
    • pytensor_ml.layers.Conv2D
    • pytensor_ml.layers.ConvTranspose1D
    • pytensor_ml.layers.ConvTranspose2D
    • pytensor_ml.layers.MaxPool1D
    • pytensor_ml.layers.MaxPool2D
    • pytensor_ml.layers.AvgPool1D
    • pytensor_ml.layers.AvgPool2D
    • pytensor_ml.layers.Upsample1D
    • pytensor_ml.layers.Upsample2D
    • pytensor_ml.layers.ZeroPad1D
    • pytensor_ml.layers.ZeroPad2D
    • pytensor_ml.layers.ConstantPad1D
    • pytensor_ml.layers.ConstantPad2D
    • pytensor_ml.layers.ReflectionPad1D
    • pytensor_ml.layers.ReflectionPad2D
    • pytensor_ml.layers.ReplicationPad1D
    • pytensor_ml.layers.ReplicationPad2D
    • pytensor_ml.layers.BatchNorm
      • pytensor_ml.layers.BatchNorm.__init__
    • pytensor_ml.layers.LayerNorm
      • pytensor_ml.layers.LayerNorm.__init__
    • pytensor_ml.layers.GroupNorm
      • pytensor_ml.layers.GroupNorm.__init__
    • pytensor_ml.layers.Dropout
      • pytensor_ml.layers.Dropout.__init__
    • pytensor_ml.layers.RNN
      • pytensor_ml.layers.RNN.__init__
    • pytensor_ml.layers.LSTM
      • pytensor_ml.layers.LSTM.__init__
    • pytensor_ml.layers.GRU
      • pytensor_ml.layers.GRU.__init__
    • pytensor_ml.layers.Bidirectional
      • pytensor_ml.layers.Bidirectional.__init__
    • pytensor_ml.layers.Recurrent
      • pytensor_ml.layers.Recurrent.__init__
    • pytensor_ml.layers.RecurrentCell
      • pytensor_ml.layers.RecurrentCell.initial_state
      • pytensor_ml.layers.RecurrentCell.step
    • pytensor_ml.layers.ElmanCell
      • pytensor_ml.layers.ElmanCell.__init__
      • pytensor_ml.layers.ElmanCell.initial_state
      • pytensor_ml.layers.ElmanCell.step
    • pytensor_ml.layers.LSTMCell
      • pytensor_ml.layers.LSTMCell.__init__
      • pytensor_ml.layers.LSTMCell.initial_state
      • pytensor_ml.layers.LSTMCell.step
    • pytensor_ml.layers.GRUCell
      • pytensor_ml.layers.GRUCell.__init__
      • pytensor_ml.layers.GRUCell.initial_state
      • pytensor_ml.layers.GRUCell.step
    • pytensor_ml.layers.MultiheadAttention
      • pytensor_ml.layers.MultiheadAttention.__init__
    • pytensor_ml.layers.CausalSelfAttention
      • pytensor_ml.layers.CausalSelfAttention.__init__
    • pytensor_ml.layers.FeedForward
      • pytensor_ml.layers.FeedForward.__init__
    • pytensor_ml.layers.TransformerBlock
      • pytensor_ml.layers.TransformerBlock.__init__
    • pytensor_ml.layers.scaled_dot_product_attention
  • Activations
    • pytensor_ml.activations.Activation
    • pytensor_ml.activations.ReLU
    • pytensor_ml.activations.LeakyReLU
      • pytensor_ml.activations.LeakyReLU.__init__
    • pytensor_ml.activations.GELU
      • pytensor_ml.activations.GELU.__init__
    • pytensor_ml.activations.QuickGELU
      • pytensor_ml.activations.QuickGELU.__init__
    • pytensor_ml.activations.Swish
      • pytensor_ml.activations.Swish.__init__
    • pytensor_ml.activations.Sigmoid
    • pytensor_ml.activations.SoftPlus
    • pytensor_ml.activations.Softmax
      • pytensor_ml.activations.Softmax.__init__
    • pytensor_ml.activations.Tanh
  • Losses
    • pytensor_ml.loss.Loss
      • pytensor_ml.loss.Loss.loss
      • pytensor_ml.loss.Loss.target_dtype
      • pytensor_ml.loss.Loss.target_ndim
    • pytensor_ml.loss.SquaredError
      • pytensor_ml.loss.SquaredError.__init__
      • pytensor_ml.loss.SquaredError.loss
    • pytensor_ml.loss.CrossEntropy
      • pytensor_ml.loss.CrossEntropy.__init__
      • pytensor_ml.loss.CrossEntropy.loss
      • pytensor_ml.loss.CrossEntropy.target_dtype
      • pytensor_ml.loss.CrossEntropy.target_ndim
    • pytensor_ml.loss.supervised_loss
  • Optimization
    • pytensor_ml.optim.compile_train
    • pytensor_ml.optim.sgd
    • pytensor_ml.optim.adam
    • pytensor_ml.optim.adamw
    • pytensor_ml.optim.nadam
    • pytensor_ml.optim.adamax
    • pytensor_ml.optim.rmsprop
    • pytensor_ml.optim.rprop
    • pytensor_ml.optim.adagrad
    • pytensor_ml.optim.adadelta
    • pytensor_ml.optim.chain
    • pytensor_ml.optim.scale
    • pytensor_ml.optim.scale_by_schedule
    • pytensor_ml.optim.add_weight_decay
    • pytensor_ml.optim.trace
    • pytensor_ml.optim.clip_by_global_norm
    • pytensor_ml.optim.clip_by_value
    • pytensor_ml.optim.skip_if
    • pytensor_ml.optim.apply_if_finite
    • pytensor_ml.optim.nonfinite
    • pytensor_ml.optim.large_step
    • pytensor_ml.optim.reduce_on_plateau
    • pytensor_ml.optim.SkipCondition
      • pytensor_ml.optim.SkipCondition.__init__
    • pytensor_ml.optim.constant_schedule
    • pytensor_ml.optim.linear_schedule
    • pytensor_ml.optim.linear_onecycle_schedule
    • pytensor_ml.optim.cosine_schedule
    • pytensor_ml.optim.exponential_schedule
    • pytensor_ml.optim.polynomial_schedule
    • pytensor_ml.optim.step_decay
    • pytensor_ml.optim.join_schedules
    • pytensor_ml.optim.counter
    • pytensor_ml.optim.get_gradients
    • pytensor_ml.optim.reuses_state
    • pytensor_ml.optim.scalar_state
    • pytensor_ml.optim.state_for
    • pytensor_ml.optim.steps_of
    • pytensor_ml.optim.to_floatx
    • pytensor_ml.optim.to_updates
    • pytensor_ml.optim.base.Transform
    • pytensor_ml.optim.base.Updates
      • pytensor_ml.optim.base.Updates.copy
      • pytensor_ml.optim.base.Updates.replacing
    • pytensor_ml.optim.base.Gradients
    • pytensor_ml.optim.base.Steps
    • pytensor_ml.optim.base.Schedule
    • pytensor_ml.optim.base.Rate
    • pytensor_ml.optim.base.LearningRate
    • pytensor_ml.optim.guards.Decision
    • pytensor_ml.optim.sgd_updates
    • pytensor_ml.optim.adam_updates
    • pytensor_ml.optim.adamw_updates
    • pytensor_ml.optim.nadam_updates
    • pytensor_ml.optim.adamax_updates
    • pytensor_ml.optim.rmsprop_updates
    • pytensor_ml.optim.rprop_updates
    • pytensor_ml.optim.adagrad_updates
    • pytensor_ml.optim.adadelta_updates
  • Parameters and initialization
    • pytensor_ml.params.TrainableParameter
    • pytensor_ml.params.NonTrainableParameter
    • pytensor_ml.params.StepCounter
      • pytensor_ml.params.StepCounter.advance
    • pytensor_ml.params.trainable
    • pytensor_ml.params.non_trainable
    • pytensor_ml.params.step_counter
    • pytensor_ml.state.Initializer
      • pytensor_ml.state.Initializer.initial_value
      • pytensor_ml.state.Initializer.sample
    • pytensor_ml.state.ZeroInitializer
      • pytensor_ml.state.ZeroInitializer.sample
    • pytensor_ml.state.OneInitializer
      • pytensor_ml.state.OneInitializer.sample
    • pytensor_ml.state.NormalInitializer
      • pytensor_ml.state.NormalInitializer.__init__
      • pytensor_ml.state.NormalInitializer.sample
    • pytensor_ml.state.UnitUniformInitializer
      • pytensor_ml.state.UnitUniformInitializer.sample
    • pytensor_ml.state.XavierNormalInitializer
      • pytensor_ml.state.XavierNormalInitializer.sample
    • pytensor_ml.state.XavierUniformInitializer
      • pytensor_ml.state.XavierUniformInitializer.sample
    • pytensor_ml.state.OrthogonalInitializer
      • pytensor_ml.state.OrthogonalInitializer.__init__
      • pytensor_ml.state.OrthogonalInitializer.sample
    • pytensor_ml.state.UnrecordedInitializer
      • pytensor_ml.state.UnrecordedInitializer.__init__
      • pytensor_ml.state.UnrecordedInitializer.sample
    • pytensor_ml.state.EmptyInitializer
      • pytensor_ml.state.EmptyInitializer.sample
    • pytensor_ml.state.initial_values_from
    • pytensor_ml.state.initialize_params
    • pytensor_ml.state.fans
  • Saving and loading
    • pytensor_ml.save_pretrained
    • pytensor_ml.from_pretrained
    • pytensor_ml.save_network
    • pytensor_ml.load_network
    • pytensor_ml.save_state
    • pytensor_ml.load_state
  • Pretrained models
    • pytensor_ml.models.architecture_name
    • pytensor_ml.models.build_from_config
    • pytensor_ml.models.register_builder
    • pytensor_ml.models.KeyMap
      • pytensor_ml.models.KeyMap.__init__
      • pytensor_ml.models.KeyMap.bind
      • pytensor_ml.models.KeyMap.key_for
      • pytensor_ml.models.KeyMap.keys
      • pytensor_ml.models.KeyMap.load
      • pytensor_ml.models.KeyMap.parameter_for
      • pytensor_ml.models.KeyMap.scope
    • pytensor_ml.models.bind_layer_norm
    • pytensor_ml.models.bind_linear
    • pytensor_ml.models.channels_last
  • Graph tools
    • pytensor_ml.pytensorf.function
    • pytensor_ml.pytensorf.compile_predict
    • pytensor_ml.pytensorf.rewrite_for_prediction
    • pytensor_ml.pytensorf.rewrite_pregrad
    • pytensor_ml.pytensorf.collect_graph_inputs
    • pytensor_ml.pytensorf.collect_data_inputs
    • pytensor_ml.pytensorf.collect_trainable_params
    • pytensor_ml.pytensorf.collect_non_trainable_params
    • pytensor_ml.pytensorf.collect_differentiable_params
    • pytensor_ml.pytensorf.collect_shared_variables
    • pytensor_ml.pytensorf.collect_step_counters
    • pytensor_ml.pytensorf.collect_clock_updates
    • pytensor_ml.pytensorf.collect_non_trainable_updates
    • pytensor_ml.pytensorf.find_rng_nodes
    • pytensor_ml.pytensorf.as_output_list
  • Utilities
    • pytensor_ml.util.DataLoader
      • pytensor_ml.util.DataLoader.__init__
      • pytensor_ml.util.DataLoader.move_cursor
      • pytensor_ml.util.DataLoader.reset
      • pytensor_ml.util.DataLoader.shuffle
  • API Reference

API Reference#

  • Model
  • Layers
  • Activations
  • Losses
  • Optimization
  • Parameters and initialization
  • Saving and loading
  • Pretrained models
  • Graph tools
  • Utilities

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