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new architecture

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This commit is contained in:
wls2002
2024-01-27 00:52:39 +08:00
parent 4efe9a53c1
commit aac41a089d
65 changed files with 1651 additions and 1783 deletions
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2
algorithm/hyperneat/substrate/__init__.py
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from .normal import NormalSubstrate, NormalSubstrateConfig
from .tools import analysis_substrate

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algorithm/hyperneat/substrate/normal.py
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from dataclasses import dataclass
from typing import Tuple
import numpy as np
from core import Substrate, State
from config import SubstrateConfig
@dataclass(frozen=True)
class NormalSubstrateConfig(SubstrateConfig):
input_coors: Tuple = ((-1, -1), (0, -1), (1, -1))
hidden_coors: Tuple = ((-1, 0), (0, 0), (1, 0))
output_coors: Tuple = ((0, 1),)
class NormalSubstrate(Substrate):
@staticmethod
def setup(config: NormalSubstrateConfig, state: State = State()):
return state.update(
input_coors=np.asarray(config.input_coors, dtype=np.float32),
output_coors=np.asarray(config.output_coors, dtype=np.float32),
hidden_coors=np.asarray(config.hidden_coors, dtype=np.float32),
)

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algorithm/hyperneat/substrate/tools.py
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import numpy as np
def analysis_substrate(state):
cd = state.input_coors.shape[1] # coordinate dimensions
si = state.input_coors.shape[0] # input coordinate size
so = state.output_coors.shape[0] # output coordinate size
sh = state.hidden_coors.shape[0] # hidden coordinate size
input_idx = np.arange(si)
output_idx = np.arange(si, si + so)
hidden_idx = np.arange(si + so, si + so + sh)
total_conns = si * sh + sh * sh + sh * so
query_coors = np.zeros((total_conns, cd * 2))
correspond_keys = np.zeros((total_conns, 2))
# connect input to hidden
aux_coors, aux_keys = cartesian_product(input_idx, hidden_idx, state.input_coors, state.hidden_coors)
query_coors[0: si * sh, :] = aux_coors
correspond_keys[0: si * sh, :] = aux_keys
# connect hidden to hidden
aux_coors, aux_keys = cartesian_product(hidden_idx, hidden_idx, state.hidden_coors, state.hidden_coors)
query_coors[si * sh: si * sh + sh * sh, :] = aux_coors
correspond_keys[si * sh: si * sh + sh * sh, :] = aux_keys
# connect hidden to output
aux_coors, aux_keys = cartesian_product(hidden_idx, output_idx, state.hidden_coors, state.output_coors)
query_coors[si * sh + sh * sh:, :] = aux_coors
correspond_keys[si * sh + sh * sh:, :] = aux_keys
return input_idx, output_idx, hidden_idx, query_coors, correspond_keys
def cartesian_product(keys1, keys2, coors1, coors2):
len1 = keys1.shape[0]
len2 = keys2.shape[0]
repeated_coors1 = np.repeat(coors1, len2, axis=0)
repeated_keys1 = np.repeat(keys1, len2)
tiled_coors2 = np.tile(coors2, (len1, 1))
tiled_keys2 = np.tile(keys2, len1)
new_coors = np.concatenate((repeated_coors1, tiled_coors2), axis=1)
correspond_keys = np.column_stack((repeated_keys1, tiled_keys2))
return new_coors, correspond_keys