def test_loop(self):
workspace.FeedBlob("cond", np.array(True))
workspace.FeedBlob("ONE", np.array(1))
workspace.FeedBlob("TWO", np.array(2))
workspace.FeedBlob("TEN", np.array(10))
workspace.FeedBlob("counter", np.array(0))
workspace.FeedBlob("output_blob", np.array(0))
loop_model = ModelHelper(name="loop_test_model")
loop_model.net.Add(["output_blob", "TWO"], "output_blob")
cond_model = ModelHelper(name="cond_test_model")
cond_model.net.Add(["counter", "ONE"], "counter")
comp_res = cond_model.net.LT(["counter", "TEN"])
cond_model.net.Copy(comp_res, "cond")
model = ModelHelper(name="test_model")
brew.loop(
model=model,
cond_blob="cond",
external_blobs=["cond", "ONE", "TWO", "TEN", "counter", "output_blob"],
loop_model=loop_model,
cond_model=cond_model)
workspace.RunNetOnce(model.param_init_net)
workspace.RunNetOnce(model.net)
output_value = workspace.FetchBlob("output_blob")
self.assertEqual(output_value, 18)
def test_loop(self):
workspace.FeedBlob("cond", np.array(True))
workspace.FeedBlob("ONE", np.array(1))
workspace.FeedBlob("TWO", np.array(2))
workspace.FeedBlob("TEN", np.array(10))
workspace.FeedBlob("counter", np.array(0))
workspace.FeedBlob("output_blob", np.array(0))
loop_model = ModelHelper(name="loop_test_model")
loop_model.net.Add(["output_blob", "TWO"], "output_blob")
cond_model = ModelHelper(name="cond_test_model")
cond_model.net.Add(["counter", "ONE"], "counter")
comp_res = cond_model.net.LT(["counter", "TEN"])
cond_model.net.Copy(comp_res, "cond")
model = ModelHelper(name="test_model")
brew.loop(model=model,
cond_blob="cond",
external_blobs=[
"cond", "ONE", "TWO", "TEN", "counter", "output_blob"
],
loop_model=loop_model,
cond_model=cond_model)
workspace.RunNetOnce(model.param_init_net)
workspace.RunNetOnce(model.net)
output_value = workspace.FetchBlob("output_blob")
self.assertEqual(output_value, 18)
model.param_init_net.ConstantFill([], ["i"], shape=[1], value=0)
model.param_init_net.ConstantFill([], ["one"], shape=[1], value=1)
model.param_init_net.ConstantFill([], ["seven"], shape=[1], value=7)
model.param_init_net.ConstantFill([], ["y"], shape=[1], value=0)
loop_model = ModelHelper(name="loop_test_model")
loop_model.net.Add(["i", "y"], ["y"])
cond_model = ModelHelper(name="cond_test_model")
cond_model.net.Add(["i", "one"], "i")
cond_model.net.LE(["i", "seven"], "cond")
brew.loop(
model=model,
cond_blob="cond", # explicitly specifying condition blob
external_blobs=["cond", "i", "one", "seven", "y"],
loop_model=loop_model,
cond_model=cond_model # condition model is optional
)
# Corresponding blob values:
# In[12]:
RunNetOnce(model.param_init_net)
RunNetOnce(model.net)
print("i = ", FetchBlob("i"))
print("y = ", FetchBlob("y"))
# ### Backpropagation
# Initialize a loop_model that represents the code to run inside of loop
loop_model = ModelHelper(name="loop_test_model")
loop_model.net.Add(["i", "y"], ["y"])
# Initialize cond_model that represents the conditional test that the loop
# abides by, as well as the incrementation step
cond_model = ModelHelper(name="cond_test_model")
cond_model.net.Add(["i", "one"], "i")
cond_model.net.LE(["i", "seven"], "cond")
# Use brew's loop operator to facilitate the creation of the loop's operator graph
brew.loop(
model=model, # main model that contains data
cond_blob="cond", # explicitly specifying condition blob
external_blobs=["cond", "i", "one", "seven", "y"], # data blobs used in execution of the loop
loop_model=loop_model, # pass loop_model
cond_model=cond_model # pass condition model (optional)
)
# Once again, let's visualize the net using the `net_drawer`.
# In[13]:
graph = net_drawer.GetPydotGraph(model.net, rankdir="LR")
display.Image(graph.create_png(), width=800)
# Finally, we'll run the `param_init_net` and `net` and print our final blob values.
model.param_init_net.ConstantFill([], ["i"], shape=[1], value=0)
model.param_init_net.ConstantFill([], ["one"], shape=[1], value=1)
model.param_init_net.ConstantFill([], ["seven"], shape=[1], value=7)
model.param_init_net.ConstantFill([], ["y"], shape=[1], value=0)
loop_model = ModelHelper(name="loop_test_model")
loop_model.net.Add(["i", "y"], ["y"])
cond_model = ModelHelper(name="cond_test_model")
cond_model.net.Add(["i", "one"], "i")
cond_model.net.LE(["i", "seven"], "cond")
brew.loop(
model=model,
cond_blob="cond", # explicitly specifying condition blob
external_blobs=["cond", "i", "one", "seven", "y"],
loop_model=loop_model,
cond_model=cond_model # condition model is optional
)
# Corresponding blob values:
# In[12]:
RunNetOnce(model.param_init_net)
RunNetOnce(model.net)
print("i = ", FetchBlob("i"))
print("y = ", FetchBlob("y"))