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egs/wsj/s5/steps/libs/nnet3/xconfig/trivial_layers.py
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# Copyright 2016 Johns Hopkins University (Dan Povey) # 2016 Vijayaditya Peddinti # 2017 Google Inc. (vpeddinti@google.com) # 2017 Vimal Manohar # Apache 2.0. """ This module contains layers that just map to a single component. """ from __future__ import print_function import math import re import sys from libs.nnet3.xconfig.basic_layers import XconfigLayerBase class XconfigRenormComponent(XconfigLayerBase): """This class is for parsing lines like 'renorm-component name=renorm1 input=Append(-3,0,3)' which will produce just a single component, of type NormalizeComponent. Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] target-rms=1.0 [The target RMS of the NormalizeComponent] """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]', 'target-rms': 1.0 } def check_configs(self): assert self.config['target-rms'] > 0.0 def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None input_dim = self.descriptors['input']['dim'] return input_dim def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] input_dim = self.descriptors['input']['dim'] target_rms = self.config['target-rms'] configs = [] line = ('component name={0} type=NormalizeComponent dim={1} target-rms={2}'.format( self.name, input_dim, target_rms)) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigBatchnormComponent(XconfigLayerBase): """This class is for parsing lines like 'batchnorm-component name=batchnorm input=Append(-3,0,3)' which will produce just a single component, of type BatchNormComponent. Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] target-rms=1.0 [The target RMS of the BatchNormComponent] include-in-init=false [You should set this to true if this precedes a `fixed-affine-layer` that is to be initialized via LDA] """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]', 'target-rms': 1.0, 'include-in-init': False} def check_configs(self): assert self.config['target-rms'] > 0.0 def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None input_dim = self.descriptors['input']['dim'] return input_dim def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) if self.config['include-in-init']: ans.append(('init', line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] input_dim = self.descriptors['input']['dim'] target_rms = self.config['target-rms'] configs = [] line = ('component name={0} type=BatchNormComponent dim={1} target-rms={2}'.format( self.name, input_dim, target_rms)) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigNoOpComponent(XconfigLayerBase): """This class is for parsing lines like 'no-op-component name=noop1 input=Append(-3,0,3)' which will produce just a single component, of type NoOpComponent. Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]' } def check_configs(self): pass def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None input_dim = self.descriptors['input']['dim'] return input_dim def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] input_dim = self.descriptors['input']['dim'] configs = [] line = ('component name={0} type=NoOpComponent dim={1}'.format( self.name, input_dim)) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigLinearComponent(XconfigLayerBase): """This class is for parsing lines like 'linear-component name=linear1 dim=1024 input=Append(-3,0,3)' which will produce just a single component, of type LinearComponent, with output-dim 1024 in this case, and input-dim determined by the dimension of the input . Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] dim=-1 [Dimension of the output] The following (shown with their effective defaults) are just passed through to the component's config line. orthonormal-constraint=0.0 max-change=0.75 l2-regularize=0.0 """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]', 'dim': -1, 'orthonormal-constraint': '', 'max-change': 0.75, 'l2-regularize': '', 'param-stddev': '', 'learning-rate-factor': '' } def check_configs(self): if self.config['dim'] <= 0: raise RuntimeError("'dim' must be specified and > 0.") def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None assert self.config['dim'] > 0 return self.config['dim'] def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] input_dim = self.descriptors['input']['dim'] output_dim = self.config['dim'] opts = '' for opt_name in ['orthonormal-constraint', 'max-change', 'l2-regularize', 'param-stddev', 'learning-rate-factor' ]: value = self.config[opt_name] if value != '': opts += ' {0}={1}'.format(opt_name, value) configs = [] line = ('component name={0} type=LinearComponent input-dim={1} output-dim={2} ' '{3}'.format(self.name, input_dim, output_dim, opts)) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigCombineFeatureMapsLayer(XconfigLayerBase): """This class is for parsing lines like 'combine-feature-maps-layer name=combine_features1 height=40 num-filters1=1 num-filters2=4' or 'combine-feature-maps-layer name=combine_features1 height=40 num-filters1=1 num-filters2=4 num-filters3=2' It produces a PermuteComponent. It expects its input to be two or three things appended together, where the first is of dimension height * num-filters1 and the second is of dimension height * num-filters2 (and the third, if present is of dimension height * num-filters2; it interpolates the filters so the output can be interpreted as a single feature map with the same height as the input and the sum of the num-filters. This is to be used in convolutional setups as part of how we combine the filterbank inputs with ivectors. """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = { 'input': '[-1]', 'num-filters1': -1, 'num-filters2': -1, 'num-filters3': 0, 'height': -1 } def check_configs(self): input_dim = self.descriptors['input']['dim'] if (self.config['num-filters1'] <= 0 or self.config['num-filters2'] <= 0 or self.config['num-filters3'] < 0 or self.config['height'] <= 0): raise RuntimeError("invalid values of num-filters1, num-filters2 and/or height") f1 = self.config['num-filters1'] f2 = self.config['num-filters2'] f3 = self.config['num-filters3'] h = self.config['height'] if input_dim != (f1 + f2 + f3) * h: raise RuntimeError("Expected input-dim={0} based on num-filters1={1}, num-filters2={2}, " "num-filters3={3} and height={4}, but got input-dim={5}".format( (f1 + f2 + f3) * h, f1, f2, f3, h, input_dim)) def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None input_dim = self.descriptors['input']['dim'] return input_dim def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] dim = self.descriptors['input']['dim'] num_filters1 = self.config['num-filters1'] num_filters2 = self.config['num-filters2'] num_filters3 = self.config['num-filters3'] # normally 0. height = self.config['height'] assert dim == (num_filters1 + num_filters2 + num_filters3) * height column_map = [] for h in range(height): for f in range(num_filters1): column_map.append(h * num_filters1 + f) for f in range(num_filters2): column_map.append(height * num_filters1 + h * num_filters2 + f) for f in range(num_filters3): column_map.append(height * (num_filters1 + num_filters2) + h * num_filters3 + f) configs = [] line = ('component name={0} type=PermuteComponent column-map={1} '.format( self.name, ','.join([str(x) for x in column_map]))) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigAffineComponent(XconfigLayerBase): """This class is for parsing lines like 'affine-component name=linear1 dim=1024 input=Append(-3,0,3)' which will produce just a single component, of type NaturalGradientAffineComponent, with output-dim 1024 in this case, and input-dim determined by the dimension of the input . Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] dim=-1 [Dimension of the output] The following (shown with their effective defaults) are just passed through to the component's config line. orthonormal-constraint=0.0 max-change=0.75 l2-regularize=0.0 """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]', 'dim': -1, 'orthonormal-constraint': '', 'max-change': 0.75, 'param-stddev': '', 'bias-stddev': '', 'l2-regularize': '' } def check_configs(self): if self.config['dim'] <= 0: raise RuntimeError("'dim' must be specified and > 0.") def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None assert self.config['dim'] > 0 return self.config['dim'] def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] input_dim = self.descriptors['input']['dim'] output_dim = self.config['dim'] opts = '' for opt_name in ['orthonormal-constraint', 'max-change', 'l2-regularize', 'param-stddev', 'bias-stddev']: value = self.config[opt_name] if value != '': opts += ' {0}={1}'.format(opt_name, value) configs = [] line = ('component name={0} type=NaturalGradientAffineComponent input-dim={1} output-dim={2} ' '{3}'.format(self.name, input_dim, output_dim, opts)) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigPerElementScaleComponent(XconfigLayerBase): """This class is for parsing lines like 'scale-component name=scale1 input=Append(-3,0,3)' which will produce just a single component, of type NaturalGradientPerElementScaleComponent, with output-dim 1024 in this case, and input-dim determined by the dimension of the input . Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] The following (shown with their effective defaults) are just passed through to the component's config line. (These defaults are mostly set in the code). max-change=0.75 l2-regularize=0.0 param-mean=1.0 # affects initialization param-stddev=0.0 # affects initialization learning-rate-factor=1.0 """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]', 'l2-regularize': '', 'max-change': 0.75, 'param-mean': '', 'param-stddev': '', 'learning-rate-factor': '' } def check_configs(self): pass def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None return self.descriptors['input']['dim'] def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] dim = self.descriptors['input']['dim'] opts = '' for opt_name in ['learning-rate-factor', 'max-change', 'l2-regularize', 'param-mean', 'param-stddev' ]: value = self.config[opt_name] if value != '': opts += ' {0}={1}'.format(opt_name, value) configs = [] line = ('component name={0} type=NaturalGradientPerElementScaleComponent dim={1} {2} ' ''.format(self.name, dim, opts)) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigPerElementOffsetComponent(XconfigLayerBase): """This class is for parsing lines like 'offset-component name=offset1 input=Append(-3,0,3)' which will produce just a single component, of type PerElementOffsetComponent, with output-dim 1024 in this case, and input-dim determined by the dimension of the input . Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] The following (shown with their effective defaults) are just passed through to the component's config line. (These defaults are mostly set in the code). max-change=0.75 l2-regularize=0.0 param-mean=0.0 # affects initialization param-stddev=0.0 # affects initialization learning-rate-factor=1.0 """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]', 'l2-regularize': '', 'max-change': 0.75, 'param-mean': '', 'param-stddev': '', 'learning-rate-factor': '' } def check_configs(self): pass def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None return self.descriptors['input']['dim'] def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_desc = self.descriptors['input']['final-string'] dim = self.descriptors['input']['dim'] opts = '' for opt_name in ['learning-rate-factor', 'max-change', 'l2-regularize', 'param-mean', 'param-stddev' ]: value = self.config[opt_name] if value != '': opts += ' {0}={1}'.format(opt_name, value) configs = [] line = ('component name={0} type=PerElementOffsetComponent dim={1} {2} ' ''.format(self.name, dim, opts)) configs.append(line) line = ('component-node name={0} component={0} input={1}'.format( self.name, input_desc)) configs.append(line) return configs class XconfigDimRangeComponent(XconfigLayerBase): """This class is for parsing lines like 'dim-range-component name=feature1 input=Append(-3,0,3) dim=40 dim-offset=0' which will produce just a single component, of part of the input. Parameters of the class, and their defaults: input='[-1]' [Descriptor giving the input of the layer.] dim=-1 [Dimension of the output.] dim-offset=0 [Dimension offset of the input.] """ def __init__(self, first_token, key_to_value, prev_names=None): XconfigLayerBase.__init__(self, first_token, key_to_value, prev_names) def set_default_configs(self): self.config = {'input': '[-1]', 'dim': -1, 'dim-offset': 0 } def check_configs(self): input_dim = self.descriptors['input']['dim'] if self.config['dim'] <= 0: raise RuntimeError("'dim' must be specified and > 0.") elif self.config['dim'] > input_dim: raise RuntimeError("'dim' must be specified and lower than the input dim.") if self.config['dim-offset'] < 0 : raise RuntimeError("'dim-offset' must be specified and >= 0.") elif self.config['dim-offset'] + self.config['dim'] > input_dim: raise RuntimeError("'dim-offset' plus output dim must be lower than the input dim.") def output_name(self, auxiliary_output=None): assert auxiliary_output is None return self.name def output_dim(self, auxiliary_output=None): assert auxiliary_output is None output_dim = self.config['dim'] if output_dim <= 0: self.config['dim'] = self.descriptors['input']['dim'] return output_dim def get_full_config(self): ans = [] config_lines = self._generate_config() for line in config_lines: for config_name in ['ref', 'final']: # we do not support user specified matrices in this layer # so 'ref' and 'final' configs are the same. ans.append((config_name, line)) return ans def _generate_config(self): # by 'descriptor_final_string' we mean a string that can appear in # config-files, i.e. it contains the 'final' names of nodes. input_node = self.descriptors['input']['final-string'] output_dim = self.config['dim'] dim_offset = self.config['dim-offset'] configs = [] line = ('dim-range-node name={0} input-node={1} dim={2} dim-offset={3}'.format( self.name, input_node, output_dim, dim_offset)) configs.append(line) return configs |