Loading cpprb/PyReplayBuffer.pyx +3 −4 Original line number Diff line number Diff line Loading @@ -2098,7 +2098,7 @@ cdef class MPReplayBuffer: self._lock_explorer() for name, b in self.buffer.items(): b[add_idx] = np.reshape(np.array(kwargs[name],copy=False,ndmin=2), b[add_idx] = np.reshape(np.array(kwargs[name], ndmin=2), self.env_dict[name]["add_shape"]) self._unlock_explorer() Loading Loading @@ -2454,8 +2454,7 @@ cdef class MPPrioritizedReplayBuffer(MPReplayBuffer): cdef const float [:] ps if priorities is not None: priorities = np.ravel(np.array(priorities,copy=False, ndmin=1,dtype=np.single)) priorities = np.ravel(np.array(priorities, ndmin=1, dtype=np.single)) if N != priorities.shape[0]: raise ValueError("`priorities` shape is incompatible") Loading Loading @@ -2485,7 +2484,7 @@ cdef class MPPrioritizedReplayBuffer(MPReplayBuffer): self._unlock_explorer_per() for name, b in self.buffer.items(): b[add_idx] = np.reshape(np.array(kwargs[name],copy=False,ndmin=2), b[add_idx] = np.reshape(np.array(kwargs[name], ndmin=2), self.env_dict[name]["add_shape"]) self._unlock_explorer() Loading Loading
cpprb/PyReplayBuffer.pyx +3 −4 Original line number Diff line number Diff line Loading @@ -2098,7 +2098,7 @@ cdef class MPReplayBuffer: self._lock_explorer() for name, b in self.buffer.items(): b[add_idx] = np.reshape(np.array(kwargs[name],copy=False,ndmin=2), b[add_idx] = np.reshape(np.array(kwargs[name], ndmin=2), self.env_dict[name]["add_shape"]) self._unlock_explorer() Loading Loading @@ -2454,8 +2454,7 @@ cdef class MPPrioritizedReplayBuffer(MPReplayBuffer): cdef const float [:] ps if priorities is not None: priorities = np.ravel(np.array(priorities,copy=False, ndmin=1,dtype=np.single)) priorities = np.ravel(np.array(priorities, ndmin=1, dtype=np.single)) if N != priorities.shape[0]: raise ValueError("`priorities` shape is incompatible") Loading Loading @@ -2485,7 +2484,7 @@ cdef class MPPrioritizedReplayBuffer(MPReplayBuffer): self._unlock_explorer_per() for name, b in self.buffer.items(): b[add_idx] = np.reshape(np.array(kwargs[name],copy=False,ndmin=2), b[add_idx] = np.reshape(np.array(kwargs[name], ndmin=2), self.env_dict[name]["add_shape"]) self._unlock_explorer() Loading