trim a little more

makslevental · Sep 28, 2022 · cf99916 · cf99916
1 parent a26f78b
commit cf99916
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Showing 3 changed files with 9 additions and 10 deletions.
diff --git a/examples/braggnn.py b/examples/braggnn.py
@@ -13,10 +13,10 @@
 class Part1(torch.nn.Module):
     def __init__(self):
         super().__init__()
-        self.cnn_layers_1 = Conv2d(1, 15, kernel_size=(3, 3), stride=(1, 1))
-        self.theta_layer = Conv2d(15, 8, kernel_size=(1, 1), stride=(1, 1))
-        self.phi_layer = Conv2d(15, 8, kernel_size=(1, 1), stride=(1, 1))
-        self.g_layer = Conv2d(15, 8, kernel_size=(1, 1), stride=(1, 1))
+        self.cnn_layers_1 = Conv2d(1, 14, kernel_size=(3, 3), stride=(1, 1))
+        self.theta_layer = Conv2d(14, 8, kernel_size=(1, 1), stride=(1, 1))
+        self.phi_layer = Conv2d(14, 8, kernel_size=(1, 1), stride=(1, 1))
+        self.g_layer = Conv2d(14, 8, kernel_size=(1, 1), stride=(1, 1))
         self.soft = SoftMax()
 
     def forward(self, inp):
@@ -37,10 +37,10 @@ def forward(self, inp):
 class Part2(torch.nn.Module):
     def __init__(self):
         super().__init__()
-        self.out_cnn = Conv2d(8, 15, kernel_size=(1, 1), stride=(1, 1))
+        self.out_cnn = Conv2d(8, 14, kernel_size=(1, 1), stride=(1, 1))
         self.cnn_layers_2 = Sequential(
             ReLU(),
-            Conv2d(15, 8, kernel_size=(3, 3), stride=(1, 1)),
+            Conv2d(14, 8, kernel_size=(3, 3), stride=(1, 1)),
             ReLU(),
         )
 
@@ -218,14 +218,14 @@ def make_braggn_part2(scale, img_size=11, simplify_weights=True):
             mod.apply(set_weights)
         z = mod(
             torch.randn(1, 8, img_size - 2, img_size - 2),
-            torch.randn(1, 15, img_size - 2, img_size - 2),
+            torch.randn(1, 14, img_size - 2, img_size - 2),
         )
         print(z.shape)
     mlir_module = compile_nn_module_to_mlir(
         mod,
         [
             ([1, 8, img_size - 2, img_size - 2], torch.float32),
-            ([1, 15, img_size - 2, img_size - 2], torch.float32),
+            ([1, 14, img_size - 2, img_size - 2], torch.float32),
         ],
     )
     return str(mlir_module)

diff --git a/scripts/make_braggnn_parts_top.py b/scripts/make_braggnn_parts_top.py
@@ -7,7 +7,7 @@
 signal_width = 12
 num_tdm_wires = 0
 num_mux_to_demux = 20
-stub_inputs = True
+stub_inputs = False
 
 
 class CombOrSeq(enum.Enum):

diff --git a/scripts/vivado_alt_synth.tcl b/scripts/vivado_alt_synth.tcl
@@ -53,7 +53,6 @@ report_methodology  -file ${reports_dir}/post_synth/methodology.rpt
 
 puts "\n================================( Place Design )================================="
 
-#set_property ALLOW_COMBINATORIAL_LOOPS TRUE [get_nets -regexp .*]
 #eval place_design -directive SSI_SpreadLogic_high -ultrathreads -fanout_opt
 eval place_design -ultrathreads -fanout_opt