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5fadb9c18e
Adding mxnet components to rl_coach architectures. - Supports PPO and DQN - Tested with CartPole_PPO and CarPole_DQN - Normalizing filters don't work right now (see #49) and are disabled in CartPole_PPO preset - Checkpointing is disabled for MXNet
62 lines
2.8 KiB
Python
62 lines
2.8 KiB
Python
from typing import Union
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from types import ModuleType
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import mxnet as mx
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from mxnet.gluon import nn
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from rl_coach.architectures.middleware_parameters import MiddlewareParameters
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from rl_coach.architectures.mxnet_components.layers import convert_layer
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from rl_coach.base_parameters import MiddlewareScheme
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nd_sym_type = Union[mx.nd.NDArray, mx.sym.Symbol]
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class Middleware(nn.HybridBlock):
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def __init__(self, params: MiddlewareParameters):
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"""
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Middleware is the middle part of the network. It takes the embeddings from the input embedders,
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after they were aggregated in some method (for example, concatenation) and passes it through a neural network
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which can be customizable but shared between the heads of the network.
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:param params: parameters object containing batchnorm, activation_function and dropout properties.
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"""
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super(Middleware, self).__init__()
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self.scheme = params.scheme
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with self.name_scope():
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self.net = nn.HybridSequential()
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if isinstance(self.scheme, MiddlewareScheme):
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blocks = self.schemes[self.scheme]
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else:
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# if scheme is specified directly, convert to MX layer if it's not a callable object
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# NOTE: if layer object is callable, it must return a gluon block when invoked
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blocks = [convert_layer(l) for l in self.scheme]
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for block in blocks:
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self.net.add(block())
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if params.batchnorm:
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self.net.add(nn.BatchNorm())
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if params.activation_function:
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self.net.add(nn.Activation(params.activation_function))
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if params.dropout:
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self.net.add(nn.Dropout(rate=params.dropout))
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@property
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def schemes(self) -> dict:
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"""
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Schemes are the pre-defined network architectures of various depths and complexities that can be used for the
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Middleware. Should be implemented in child classes, and are used to create Block when Middleware is initialised.
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:return: dictionary of schemes, with key of type MiddlewareScheme enum and value being list of mxnet.gluon.Block.
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"""
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raise NotImplementedError("Inheriting embedder must define schemes matching its allowed default "
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"configurations.")
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def hybrid_forward(self, F: ModuleType, x: nd_sym_type, *args, **kwargs) -> nd_sym_type:
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"""
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Used for forward pass through middleware network.
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:param F: backend api, either `mxnet.nd` or `mxnet.sym` (if block has been hybridized).
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:param x: state embedding, of shape (batch_size, in_channels).
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:return: state middleware embedding, where shape is (batch_size, channels).
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"""
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return self.net(x)
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