| |
|
| |
|
| | import numpy as np |
| | from caffe2.python import core, workspace |
| | from caffe2.quantization.server import dnnlowp_pybind11 |
| |
|
| |
|
| | 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) |
| |
|
