Learn more  » Push, build, and install  RubyGems npm packages Python packages Maven artifacts PHP packages Go Modules Bower components Debian packages RPM packages NuGet packages

neilisaac / torch   python

Repository URL to install this package:

/ quantization / server / observer_test.py



import numpy as np
from caffe2.python import core, workspace
from caffe2.quantization.server import dnnlowp_pybind11  # type: ignore[attr-defined]


net = core.Net("test_net")

X = np.array([[1, 2], [3, 4]]).astype(np.float32)
W = np.array([[5, 6], [7, 8]]).astype(np.float32)
b = np.array([0, 1]).astype(np.float32)

workspace.FeedBlob("X", X)
workspace.FeedBlob("W", W)
workspace.FeedBlob("b", b)

Y = net.FC(["X", "W", "b"], ["Y"])

dnnlowp_pybind11.ObserveMinMaxOfOutput("test_net.minmax", 1)
workspace.CreateNet(net)
workspace.RunNet(net)
print(workspace.FetchBlob("Y"))

workspace.ResetWorkspace()

workspace.FeedBlob("X", X)
workspace.FeedBlob("W", W)
workspace.FeedBlob("b", b)

dnnlowp_pybind11.ObserveHistogramOfOutput("test_net.hist", 1)
workspace.CreateNet(net)
workspace.RunNet(net)


workspace.FeedBlob("X", X)
workspace.FeedBlob("W", W)
workspace.FeedBlob("b", b)

dnnlowp_pybind11.AddOutputColumnMaxHistogramObserver(
    net._net.name, "test_net._col_max_hist", ["Y"]
)
workspace.RunNet(net)