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|
# Owner(s): ["oncall: quantization"]
from .common import AOMigrationTestCase
class TestAOMigrationNNQuantized(AOMigrationTestCase):
def test_functional_import(self):
r"""Tests the migration of the torch.nn.quantized.functional"""
function_list = [
"avg_pool2d",
"avg_pool3d",
"adaptive_avg_pool2d",
"adaptive_avg_pool3d",
"conv1d",
"conv2d",
"conv3d",
"interpolate",
"linear",
"max_pool1d",
"max_pool2d",
"celu",
"leaky_relu",
"hardtanh",
"hardswish",
"threshold",
"elu",
"hardsigmoid",
"clamp",
"upsample",
"upsample_bilinear",
"upsample_nearest",
]
self._test_function_import("functional", function_list, base="nn.quantized")
def test_modules_import(self):
module_list = [
# Modules
"BatchNorm2d",
"BatchNorm3d",
"Conv1d",
"Conv2d",
"Conv3d",
"ConvTranspose1d",
"ConvTranspose2d",
"ConvTranspose3d",
"DeQuantize",
"ELU",
"Embedding",
"EmbeddingBag",
"GroupNorm",
"Hardswish",
"InstanceNorm1d",
"InstanceNorm2d",
"InstanceNorm3d",
"LayerNorm",
"LeakyReLU",
"Linear",
"MaxPool2d",
"Quantize",
"ReLU6",
"Sigmoid",
"Softmax",
"Dropout",
# Wrapper modules
"FloatFunctional",
"FXFloatFunctional",
"QFunctional",
]
self._test_function_import("modules", module_list, base="nn.quantized")
def test_modules_activation(self):
function_list = [
"ReLU6",
"Hardswish",
"ELU",
"LeakyReLU",
"Sigmoid",
"Softmax",
]
self._test_function_import(
"activation", function_list, base="nn.quantized.modules"
)
def test_modules_batchnorm(self):
function_list = [
"BatchNorm2d",
"BatchNorm3d",
]
self._test_function_import(
"batchnorm", function_list, base="nn.quantized.modules"
)
def test_modules_conv(self):
function_list = [
"_reverse_repeat_padding",
"Conv1d",
"Conv2d",
"Conv3d",
"ConvTranspose1d",
"ConvTranspose2d",
"ConvTranspose3d",
]
self._test_function_import("conv", function_list, base="nn.quantized.modules")
def test_modules_dropout(self):
function_list = [
"Dropout",
]
self._test_function_import(
"dropout", function_list, base="nn.quantized.modules"
)
def test_modules_embedding_ops(self):
function_list = [
"EmbeddingPackedParams",
"Embedding",
"EmbeddingBag",
]
self._test_function_import(
"embedding_ops", function_list, base="nn.quantized.modules"
)
def test_modules_functional_modules(self):
function_list = [
"FloatFunctional",
"FXFloatFunctional",
"QFunctional",
]
self._test_function_import(
"functional_modules", function_list, base="nn.quantized.modules"
)
def test_modules_linear(self):
function_list = [
"Linear",
"LinearPackedParams",
]
self._test_function_import("linear", function_list, base="nn.quantized.modules")
def test_modules_normalization(self):
function_list = [
"LayerNorm",
"GroupNorm",
"InstanceNorm1d",
"InstanceNorm2d",
"InstanceNorm3d",
]
self._test_function_import(
"normalization", function_list, base="nn.quantized.modules"
)
def test_modules_utils(self):
function_list = [
"_ntuple_from_first",
"_pair_from_first",
"_quantize_weight",
"_hide_packed_params_repr",
"WeightedQuantizedModule",
]
self._test_function_import("utils", function_list, base="nn.quantized.modules")
def test_import_nn_quantized_dynamic_import(self):
module_list = [
# Modules
"Linear",
"LSTM",
"GRU",
"LSTMCell",
"RNNCell",
"GRUCell",
"Conv1d",
"Conv2d",
"Conv3d",
"ConvTranspose1d",
"ConvTranspose2d",
"ConvTranspose3d",
]
self._test_function_import("dynamic", module_list, base="nn.quantized")
def test_import_nn_quantizable_activation(self):
module_list = [
# Modules
"MultiheadAttention",
]
self._test_function_import(
"activation", module_list, base="nn.quantizable.modules"
)
def test_import_nn_quantizable_rnn(self):
module_list = [
# Modules
"LSTM",
"LSTMCell",
]
self._test_function_import("rnn", module_list, base="nn.quantizable.modules")
def test_import_nn_qat_conv(self):
module_list = [
"Conv1d",
"Conv2d",
"Conv3d",
]
self._test_function_import("conv", module_list, base="nn.qat.modules")
def test_import_nn_qat_embedding_ops(self):
module_list = [
"Embedding",
"EmbeddingBag",
]
self._test_function_import("embedding_ops", module_list, base="nn.qat.modules")
def test_import_nn_qat_linear(self):
module_list = [
"Linear",
]
self._test_function_import("linear", module_list, base="nn.qat.modules")
def test_import_nn_qat_dynamic_linear(self):
module_list = [
"Linear",
]
self._test_function_import("linear", module_list, base="nn.qat.dynamic.modules")
class TestAOMigrationNNIntrinsic(AOMigrationTestCase):
def test_modules_import_nn_intrinsic(self):
module_list = [
# Modules
"_FusedModule",
"ConvBn1d",
"ConvBn2d",
"ConvBn3d",
"ConvBnReLU1d",
"ConvBnReLU2d",
"ConvBnReLU3d",
"ConvReLU1d",
"ConvReLU2d",
"ConvReLU3d",
"LinearReLU",
"BNReLU2d",
"BNReLU3d",
"LinearBn1d",
]
self._test_function_import("intrinsic", module_list, base="nn")
def test_modules_nn_intrinsic_fused(self):
function_list = [
"_FusedModule",
"ConvBn1d",
"ConvBn2d",
"ConvBn3d",
"ConvBnReLU1d",
"ConvBnReLU2d",
"ConvBnReLU3d",
"ConvReLU1d",
"ConvReLU2d",
"ConvReLU3d",
"LinearReLU",
"BNReLU2d",
"BNReLU3d",
"LinearBn1d",
]
self._test_function_import("fused", function_list, base="nn.intrinsic.modules")
def test_modules_import_nn_intrinsic_qat(self):
module_list = [
"LinearReLU",
"LinearBn1d",
"ConvReLU1d",
"ConvReLU2d",
"ConvReLU3d",
"ConvBn1d",
"ConvBn2d",
"ConvBn3d",
"ConvBnReLU1d",
"ConvBnReLU2d",
"ConvBnReLU3d",
"update_bn_stats",
"freeze_bn_stats",
]
self._test_function_import("qat", module_list, base="nn.intrinsic")
def test_modules_intrinsic_qat_conv_fused(self):
function_list = [
"ConvBn1d",
"ConvBnReLU1d",
"ConvReLU1d",
"ConvBn2d",
"ConvBnReLU2d",
"ConvReLU2d",
"ConvBn3d",
"ConvBnReLU3d",
"ConvReLU3d",
"update_bn_stats",
"freeze_bn_stats",
]
self._test_function_import(
"conv_fused", function_list, base="nn.intrinsic.qat.modules"
)
def test_modules_intrinsic_qat_linear_fused(self):
function_list = [
"LinearBn1d",
]
self._test_function_import(
"linear_fused", function_list, base="nn.intrinsic.qat.modules"
)
def test_modules_intrinsic_qat_linear_relu(self):
function_list = [
"LinearReLU",
]
self._test_function_import(
"linear_relu", function_list, base="nn.intrinsic.qat.modules"
)
def test_modules_import_nn_intrinsic_quantized(self):
module_list = [
"BNReLU2d",
"BNReLU3d",
"ConvReLU1d",
"ConvReLU2d",
"ConvReLU3d",
"LinearReLU",
]
self._test_function_import("quantized", module_list, base="nn.intrinsic")
def test_modules_intrinsic_quantized_bn_relu(self):
function_list = [
"BNReLU2d",
"BNReLU3d",
]
self._test_function_import(
"bn_relu", function_list, base="nn.intrinsic.quantized.modules"
)
def test_modules_intrinsic_quantized_conv_relu(self):
function_list = [
"ConvReLU1d",
"ConvReLU2d",
"ConvReLU3d",
]
self._test_function_import(
"conv_relu", function_list, base="nn.intrinsic.quantized.modules"
)
def test_modules_intrinsic_quantized_linear_relu(self):
function_list = [
"LinearReLU",
]
self._test_function_import(
"linear_relu", function_list, base="nn.intrinsic.quantized.modules"
)
def test_modules_no_import_nn_intrinsic_quantized_dynamic(self):
# TODO(future PR): generalize this
import torch
_ = torch.ao.nn.intrinsic.quantized.dynamic
_ = torch.nn.intrinsic.quantized.dynamic
|
