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# RUN: %PYTHON %s | FileCheck %s
import numpy as np
from mlir.ir import *
from mlir.dialects import quant
def run(f):
print("\nTEST:", f.__name__)
f()
return f
# CHECK-LABEL: TEST: test_type_hierarchy
@run
def test_type_hierarchy():
with Context():
i8 = IntegerType.get_signless(8)
any = Type.parse("!quant.any<i8<-8:7>:f32>")
uniform = Type.parse("!quant.uniform<i8<-8:7>:f32, 0.99872:127>")
per_axis = Type.parse("!quant.uniform<i8:f32:1, {2.0e+2,0.99872:120}>")
sub_channel = Type.parse(
"!quant.uniform<i8:f32:{0:1, 1:2}, {{2.0:10, 3.0:20}, {4.0:30, 5.0:40}}>"
)
calibrated = Type.parse("!quant.calibrated<f32<-0.998:1.2321>>")
assert not quant.QuantizedType.isinstance(i8)
assert quant.QuantizedType.isinstance(any)
assert quant.QuantizedType.isinstance(uniform)
assert quant.QuantizedType.isinstance(per_axis)
assert quant.QuantizedType.isinstance(sub_channel)
assert quant.QuantizedType.isinstance(calibrated)
assert quant.AnyQuantizedType.isinstance(any)
assert quant.UniformQuantizedType.isinstance(uniform)
assert quant.UniformQuantizedPerAxisType.isinstance(per_axis)
assert quant.UniformQuantizedSubChannelType.isinstance(sub_channel)
assert quant.CalibratedQuantizedType.isinstance(calibrated)
assert not quant.AnyQuantizedType.isinstance(uniform)
assert not quant.UniformQuantizedType.isinstance(per_axis)
assert not quant.UniformQuantizedType.isinstance(sub_channel)
assert not quant.UniformQuantizedPerAxisType.isinstance(sub_channel)
# CHECK-LABEL: TEST: test_any_quantized_type
@run
def test_any_quantized_type():
with Context():
i8 = IntegerType.get_signless(8)
f32 = F32Type.get()
any = quant.AnyQuantizedType.get(
quant.QuantizedType.FLAG_SIGNED, i8, f32, -8, 7
)
# CHECK: flags: 1
print(f"flags: {any.flags}")
# CHECK: signed: True
print(f"signed: {any.is_signed}")
# CHECK: storage type: i8
print(f"storage type: {any.storage_type}")
# CHECK: expressed type: f32
print(f"expressed type: {any.expressed_type}")
# CHECK: storage min: -8
print(f"storage min: {any.storage_type_min}")
# CHECK: storage max: 7
print(f"storage max: {any.storage_type_max}")
# CHECK: storage width: 8
print(f"storage width: {any.storage_type_integral_width}")
# CHECK: quantized element type: !quant.any<i8<-8:7>:f32>
print(f"quantized element type: {any.quantized_element_type}")
# CHECK: !quant.any<i8<-8:7>:f32>
print(any)
assert any == Type.parse("!quant.any<i8<-8:7>:f32>")
# CHECK-LABEL: TEST: test_uniform_type
@run
def test_uniform_type():
with Context():
i8 = IntegerType.get_signless(8)
f32 = F32Type.get()
uniform = quant.UniformQuantizedType.get(
quant.UniformQuantizedType.FLAG_SIGNED, i8, f32, 0.99872, 127, -8, 7
)
# CHECK: scale: 0.99872
print(f"scale: {uniform.scale}")
# CHECK: zero point: 127
print(f"zero point: {uniform.zero_point}")
# CHECK: fixed point: False
print(f"fixed point: {uniform.is_fixed_point}")
# CHECK: !quant.uniform<i8<-8:7>:f32, 9.987200e-01:127>
print(uniform)
assert uniform == Type.parse("!quant.uniform<i8<-8:7>:f32, 0.99872:127>")
# CHECK-LABEL: TEST: test_uniform_per_axis_type
@run
def test_uniform_per_axis_type():
with Context():
i8 = IntegerType.get_signless(8)
f32 = F32Type.get()
per_axis = quant.UniformQuantizedPerAxisType.get(
quant.QuantizedType.FLAG_SIGNED,
i8,
f32,
[200, 0.99872],
[0, 120],
quantized_dimension=1,
storage_type_min=quant.QuantizedType.default_minimum_for_integer(
is_signed=True, integral_width=8
),
storage_type_max=quant.QuantizedType.default_maximum_for_integer(
is_signed=True, integral_width=8
),
)
# CHECK: scales: [200.0, 0.99872]
print(f"scales: {per_axis.scales}")
# CHECK: zero_points: [0, 120]
print(f"zero_points: {per_axis.zero_points}")
# CHECK: quantized dim: 1
print(f"quantized dim: {per_axis.quantized_dimension}")
# CHECK: fixed point: False
print(f"fixed point: {per_axis.is_fixed_point}")
# CHECK: !quant.uniform<i8:f32:1, {2.000000e+02,9.987200e-01:120}>
print(per_axis)
assert per_axis == Type.parse("!quant.uniform<i8:f32:1, {2.0e+2,0.99872:120}>")
# CHECK-LABEL: TEST: test_uniform_sub_channel_type
@run
def test_uniform_sub_channel_type():
with Context():
i8 = IntegerType.get_signless(8)
f32 = F32Type.get()
sub_channel = quant.UniformQuantizedSubChannelType.get(
quant.QuantizedType.FLAG_SIGNED,
i8,
f32,
DenseElementsAttr.get(
np.asarray([2.0, 3.0, 4.0, 5.0], np.float32).reshape(2, 2)
),
DenseElementsAttr.get(np.asarray([10, 20, 30, 40], np.int8).reshape(2, 2)),
[0, 1],
[1, 2],
storage_type_min=quant.QuantizedType.default_minimum_for_integer(
is_signed=True, integral_width=8
),
storage_type_max=quant.QuantizedType.default_maximum_for_integer(
is_signed=True, integral_width=8
),
)
# CHECK: quantized dimensions: [0, 1]
print(f"quantized dimensions: {sub_channel.quantized_dimensions}")
# CHECK: block sizes: [1, 2]
print(f"block sizes: {sub_channel.block_sizes}")
# CHECK: scales: {{\[}}[2. 3.]
# CHECK: [4. 5.]]
print(f"scales: {np.asarray(sub_channel.scales)}")
# CHECK: zero-points: {{\[}}[10 20]
# CHECK: [30 40]]
print(f"zero-points: {np.asarray(sub_channel.zero_points)}")
# CHECK: !quant.uniform<i8:f32:{0:1, 1:2}, {{\{}}{2.000000e+00:10, 3.000000e+00:20}, {4.000000e+00:30, 5.000000e+00:40}}>
print(sub_channel)
assert sub_channel == Type.parse(
"!quant.uniform<i8:f32:{0:1, 1:2},{{2.0:10, 3.0:20}, {4.0:30, 5.0:40}}>"
)
# CHECK-LABEL: TEST: test_calibrated_type
@run
def test_calibrated_type():
with Context():
f32 = F32Type.get()
calibrated = quant.CalibratedQuantizedType.get(f32, -0.998, 1.2321)
# CHECK: min: -0.998
print(f"min: {calibrated.min}")
# CHECK: max: 1.2321
print(f"max: {calibrated.max}")
# CHECK: !quant.calibrated<f32<-0.998:1.232100e+00>>
print(calibrated)
assert calibrated == Type.parse("!quant.calibrated<f32<-0.998:1.2321>>")
|
