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# Must happen before importing caffe2.python.*
import caffe2.python.fakelowp.init_shared_libs # noqa
import datetime
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace
from caffe2.python.onnx.onnxifi import onnxifi_caffe2_net
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import settings
workspace.GlobalInit(
[
"caffe2",
"--glow_global_fp16=0",
"--glow_global_fused_scale_offset_fp16=0",
"--glow_global_force_sls_fp16_accum=0",
]
)
class QuantTest(serial.SerializedTestCase):
@settings(deadline=datetime.timedelta(seconds=10))
def test_dequantize(self):
pred_net = caffe2_pb2.NetDef()
pred_net.name = "pred"
pred_net.external_input.append("X")
pred_net.external_output.append("Y")
x_scale = 0.10000000149011612
pred_net.op.add().CopyFrom(
core.CreateOperator(
"Int8Quantize", ["X"], ["I"], Y_scale=x_scale, Y_zero_point=0
)
)
pred_net.op.add().CopyFrom(
core.CreateOperator(
"Int8Dequantize", ["I"], ["Y"],
)
)
print(pred_net)
X = np.asarray([[1, 0], [0, 1]]).astype(np.float32)
workspace.FeedBlob("X", X)
workspace.CreateNet(pred_net)
workspace.RunNet(pred_net.name)
Y_ref = workspace.FetchBlob("Y")
workspace.ResetWorkspace()
pred_net_onnxified = onnxifi_caffe2_net(
pred_net,
{"X": [5, 2]},
debug=True,
adjust_batch=True,
block_list=[0],
use_onnx=False,
)
num_onnxified_ops = sum(
1 if o.type == "Onnxifi" else 0 for o in pred_net_onnxified.op
)
np.testing.assert_equal(len(pred_net_onnxified.op), 2)
np.testing.assert_equal(num_onnxified_ops, 1)
workspace.FeedBlob("X", X)
workspace.CreateNet(pred_net_onnxified)
workspace.RunNet(pred_net_onnxified.name)
Y_glow = workspace.FetchBlob("Y")
np.testing.assert_equal(Y_ref, Y_glow)
@settings(deadline=datetime.timedelta(seconds=20))
def test_quantize(self):
pred_net = caffe2_pb2.NetDef()
pred_net.name = "pred"
pred_net.external_input.append("X")
pred_net.external_output.append("Y")
x_scale = 0.10000000149011612
pred_net.op.add().CopyFrom(
core.CreateOperator(
"Int8Quantize", ["X"], ["Y"], Y_scale=x_scale, Y_zero_point=0
)
)
print(pred_net)
X = np.asarray([[1, 0], [0, 1]]).astype(np.float32)
workspace.FeedBlob("X", X)
workspace.RunNetOnce(pred_net)
Y_ref = workspace.FetchInt8Blob("Y")
workspace.ResetWorkspace()
pred_net_onnxified = onnxifi_caffe2_net(
pred_net,
{"X": [2, 2]},
debug=True,
adjust_batch=False,
use_onnx=False,
)
num_onnxified_ops = sum(
1 if o.type == "Onnxifi" else 0 for o in pred_net_onnxified.op
)
np.testing.assert_equal(num_onnxified_ops, 1)
workspace.FeedBlob("X", X)
workspace.CreateNet(pred_net_onnxified)
workspace.RunNet(pred_net_onnxified.name)
Y_glow = workspace.FetchInt8Blob("Y")
np.testing.assert_equal(Y_ref.data, Y_glow.data)
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