From 452b2a3a9ad1bca6530f5102c717addd6d3f62d4 Mon Sep 17 00:00:00 2001
From: He Sichao <1310722434@qq.com>
Date: Thu, 30 May 2024 12:40:45 +0800
Subject: [PATCH] Update linear.py

---
 brainpy/_src/dnn/linear.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/brainpy/_src/dnn/linear.py b/brainpy/_src/dnn/linear.py
index 03398766..729fdc70 100644
--- a/brainpy/_src/dnn/linear.py
+++ b/brainpy/_src/dnn/linear.py
@@ -980,28 +980,28 @@ def __init__(
     self.sharding = sharding
 
 
-class JitFPHomoLinear(Layer):
+class JitFPHomoLayer(Layer):
   def get_conn_matrix(self):
     return bm.jitconn.get_conn_matrix(self.prob, self.seed,
                                       shape=(self.num_out, self.num_in),
                                       transpose=self.transpose,
                                       outdim_parallel=not self.atomic)
 
-class JitFPUniformLinear(Layer):
+class JitFPUniformLayer(Layer):
   def get_conn_matrix(self):
     return bm.jitconn.get_uniform_weight_matrix(self.w_low, self.w_high, self.prob, self.seed,
                                       shape=(self.num_out, self.num_in),
                                       transpose=self.transpose,
                                       outdim_parallel=not self.atomic)
 
-class JitFPNormalLinear(Layer):
+class JitFPNormalLayer(Layer):
   def get_conn_matrix(self):
     return bm.jitconn.get_normal_weight_matrix(self.w_mu, self.w_sigma, self.prob, self.seed,
                                       shape=(self.num_out, self.num_in),
                                       transpose=self.transpose,
                                       outdim_parallel=not self.atomic)
 
-class JitFPHomoLinear(JitFPHomoLinear):
+class JitFPHomoLinear(JitFPHomoLayer):
   r"""Synaptic matrix multiplication with the just-in-time connectivity.
 
   It performs the computation of:
@@ -1080,7 +1080,7 @@ def _batch_mv(self, x):
                                    outdim_parallel=not self.atomic)
 
 
-class JitFPUniformLinear(JitFPUniformLinear):
+class JitFPUniformLinear(JitFPUniformLayer):
   r"""Synaptic matrix multiplication with the just-in-time connectivity.
 
   It performs the computation of:
@@ -1160,7 +1160,7 @@ def _batch_mv(self, x):
                                       outdim_parallel=not self.atomic)
 
 
-class JitFPNormalLinear(JitFPNormalLinear):
+class JitFPNormalLinear(JitFPNormalLayer):
   r"""Synaptic matrix multiplication with the just-in-time connectivity.
 
   It performs the computation of:
@@ -1240,7 +1240,7 @@ def _batch_mv(self, x):
                                      outdim_parallel=not self.atomic)
 
 
-class EventJitFPHomoLinear(JitFPHomoLinear):
+class EventJitFPHomoLinear(JitFPHomoLayer):
   r"""Synaptic matrix multiplication with the just-in-time connectivity.
 
   It performs the computation of:
@@ -1319,7 +1319,7 @@ def _batch_mv(self, x):
                                          outdim_parallel=not self.atomic)
 
 
-class EventJitFPUniformLinear(JitFPUniformLinear):
+class EventJitFPUniformLinear(JitFPUniformLayer):
   r"""Synaptic matrix multiplication with the just-in-time connectivity.
 
   It performs the computation of:
@@ -1399,7 +1399,7 @@ def _batch_mv(self, x):
                                             outdim_parallel=not self.atomic)
 
 
-class EventJitFPNormalLinear(JitFPNormalLinear):
+class EventJitFPNormalLinear(JitFPNormalLayer):
   r"""Synaptic matrix multiplication with the just-in-time connectivity.
 
   It performs the computation of: