- initroduced types: BB-RBM GB-RBM, GG-RBM as property of entity

- training simplification and for clarity: added specialized cd_funcs for each entity type

src/rbm/entity.py

@@ -1,6 +1,6 @@
 from .state import RbmState
 from .matrix import prob, Mat
-
+from enum import Enum
 class EntityParams:
 	def __init__(self, do_gaussian_visible: bool = False, do_gaussian_hidden: bool = False, num_gibbs_samples: int = 1):
 		# Entity parameters
@@ -21,11 +21,29 @@ class EntityParams:
 		return obj
 
 class Entity:
+	class Type(Enum):
+		BB_RBM = "BB-RBM"
+		BG_RBM = "BG-RBM"
+		GB_RBM = "GB-RBM"
+		GG_RBM = "GG-RBM"
+
 	def __init__(self, shape: tuple[int, int], params: EntityParams):
 		self.shape = shape
 		self.params = params
 		self.state = RbmState.from_layer_params(shape)
 		self.grad = RbmState.from_layer_params(shape)
+		self.type = None
+		if params.do_gaussian_visible:
+			if params.do_gaussian_hidden:
+				self.type = Entity.Type.GG_RBM
+			else:
+				self.type = Entity.Type.GB_RBM
+		else:
+			if params.do_gaussian_hidden:
+				self.type = Entity.Type.BG_RBM
+			else:
+				self.type = Entity.Type.BB_RBM
+
 
 	def __call__(self, x: Mat):
 		return self.forward(x)
@@ -72,6 +90,7 @@ class Entity:
 
 		return prob(state)
 
+
 	def _h_to_pv(self, h: Mat) -> Mat:
 		state = self.state.h_to_v(h)
 		if self.params.do_gaussian_visible:
@@ -79,5 +98,14 @@ class Entity:
 
 		return prob(state)
 
+	def h_given_v(self, v: Mat) -> Mat:
+		state = self.state.v_to_h(v)
+		return state
+
+
+	def v_given_h(self, h: Mat) -> Mat:
+		state = self.state.h_to_v(h)
+		return state
+
 if __name__ == "__main__":
 	print("Test: [passed]")