[relay][frontend] Return Module from get_workload (apache#3483)

* [relay][frontend] Return Module from get_workload * pass entry_func to autotvm * disable tune * add property to module * mod.entry_func to main * .main -> mod["main"] * fix
tqchen · Jul 6, 2019 · 1cad4c6 · 1cad4c6
1 parent 33b2f06
commit 1cad4c6
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Showing 4 changed files with 4 additions and 4 deletions.
diff --git a/python/vta/top/graphpack.py b/python/vta/top/graphpack.py
@@ -26,7 +26,7 @@ def run_opt_pass(expr, opt_pass):
     assert isinstance(opt_pass, transform.Pass)
     mod = relay.Module.from_expr(expr)
     mod = opt_pass(mod)
-    entry = mod[mod.entry_func]
+    entry = mod["main"]
     return entry if isinstance(expr, relay.Function) else entry.body
 
 def _to_shape(shape):

diff --git a/scripts/tune_resnet.py b/scripts/tune_resnet.py
@@ -127,7 +127,7 @@ def compile_network(opt, env, target):
     # Perform quantization in Relay
     with relay.quantize.qconfig(global_scale=8.0,
                                 skip_conv_layers=[0]):
-        relay_prog = relay.quantize.quantize(mod[mod.entry_func], params=params)
+        relay_prog = relay.quantize.quantize(mod["main"], params=params)
 
     # Perform graph packing and constant folding for VTA target
     if target.device_name == "vta":

diff --git a/tutorials/autotvm/tune_relay_vta.py b/tutorials/autotvm/tune_relay_vta.py
@@ -91,7 +91,7 @@ def compile_network(env, target, model, start_pack, stop_pack):
     # Perform quantization in Relay
     with relay.quantize.qconfig(global_scale=8.0,
                                 skip_conv_layers=[0]):
-        relay_prog = relay.quantize.quantize(mod[mod.entry_func], params=params)
+        relay_prog = relay.quantize.quantize(mod["main"], params=params)
 
     # Perform graph packing and constant folding for VTA target
     if target.device_name == "vta":

diff --git a/tutorials/frontend/deploy_resnet_on_vta.py b/tutorials/frontend/deploy_resnet_on_vta.py
@@ -160,7 +160,7 @@
     # Perform quantization in Relay
     with relay.quantize.qconfig(global_scale=8.0,
                                 skip_conv_layers=[0]):
-        relay_prog = relay.quantize.quantize(mod[mod.entry_func], params=params)
+        relay_prog = relay.quantize.quantize(mod["main"], params=params)
 
     # Perform graph packing and constant folding for VTA target
     if target.device_name == "vta":