refactored
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+1
-1
@@ -2,7 +2,7 @@ import numpy as np
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from collections.abc import Callable
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from collections.abc import Callable
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from params import RbmParams
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from params import RbmParams
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from helper import sample, gaussian
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from matrix import sample, gaussian
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def cd_jens(v_states: np.ndarray, params: RbmParams, v_to_ph: Callable, h_to_pv: Callable):
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def cd_jens(v_states: np.ndarray, params: RbmParams, v_to_ph: Callable, h_to_pv: Callable):
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v_probs = v_states
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v_probs = v_states
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+1
-1
@@ -2,7 +2,7 @@ import numpy as np
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from collections.abc import Callable
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from collections.abc import Callable
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from params import RbmParams
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from params import RbmParams
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from state import RbmState
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from state import RbmState
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from helper import sample, prob, uniform, rms_error_accu
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from matrix import sample, prob, rms_error_accu
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from status import Status
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from status import Status
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from cd_train import cd_jens
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from cd_train import cd_jens
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+3
-3
@@ -1,5 +1,5 @@
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import numpy as np
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import numpy as np
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from helper import uniform
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from matrix import uniform
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class RbmState:
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class RbmState:
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@@ -33,10 +33,10 @@ class RbmState:
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return obj
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return obj
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def v_to_h(self, visible: np.ndarray) -> np.ndarray:
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def v_to_h(self, visible: np.ndarray) -> np.ndarray:
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return np.vecmat(visible, self.w_hv) + self.b_h
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return np.dot(visible, self.w_hv) + self.b_h
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def h_to_v(self, hidden: np.ndarray) -> np.ndarray:
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def h_to_v(self, hidden: np.ndarray) -> np.ndarray:
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return np.vecmat(hidden, np.transpose(self.w_hv)) + self.b_v
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return np.dot(hidden, np.transpose(self.w_hv)) + self.b_v
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def to_file(self, filename: str):
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def to_file(self, filename: str):
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np.savez(filename, whv=self.w_hv, bv=self.b_v, bh=self.b_h)
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np.savez(filename, whv=self.w_hv, bv=self.b_v, bh=self.b_h)
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