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chore(compiler): refactor e2e tlu tests to use dynamic lut.

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This commit is contained in:
aPere3
2023-08-29 11:28:20 +02:00
committed by Alexandre Péré
parent 229bbc2327
commit b58821b1d1
1 changed files with 66 additions and 12 deletions
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78
compilers/concrete-compiler/compiler/tests/end_to_end_fixture/end_to_end_apply_lookup_table_gen.py
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@@ -7,6 +7,19 @@ from end_to_end_linalg_leveled_gen import P_ERROR
PRECISION_FORCE_CRT = 9
def get_lut_integer_type(p):
if p <= 8:
return "i8"
if p <= 16:
return "i16"
if p <= 32:
return "i32"
if p <= 64:
return "i64"
else:
raise Exception("Unexpected precision")
def generate(args):
print("# /!\ DO NOT EDIT MANUALLY THIS FILE MANUALLY")
print("# /!\ THIS FILE HAS BEEN GENERATED")
@@ -15,13 +28,13 @@ def generate(args):
for p in args.bitwidth:
max_value = (2 ** p) - 1
random_lut = np.random.randint(max_value+1, size=2**p)
itype = get_lut_integer_type(p)
print(f"description: apply_lookup_table_{p}bits")
print("program: |")
print(
f" func.func @main(%arg0: !FHE.eint<{p}>) -> !FHE.eint<{p}> {{")
print(f" %tlu = arith.constant dense<[{','.join(map(str, random_lut))}]> : tensor<{2**p}xi64>")
f" func.func @main(%arg0: !FHE.eint<{p}>, %arg1: tensor<{2**p}x{itype}>) -> !FHE.eint<{p}> {{")
print(
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %tlu): (!FHE.eint<{p}>, tensor<{2**p}xi64>) -> (!FHE.eint<{p}>)")
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %arg1): (!FHE.eint<{p}>, tensor<{2**p}x{itype}>) -> (!FHE.eint<{p}>)")
print(f" return %1: !FHE.eint<{p}>")
print(" }")
if p >= PRECISION_FORCE_CRT:
@@ -31,15 +44,21 @@ def generate(args):
print(" - inputs:")
random_i = np.random.randint(max_value)
print(f" - scalar: {random_i}")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[random_i]}")
if not args.minimal:
print(" - inputs:")
print(" - scalar: 0")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[0]}")
print(" - inputs:")
print(f" - scalar: {max_value}")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[max_value]}")
print("---")
@@ -49,13 +68,13 @@ def generate(args):
upper_bound = (2 ** (p-1)) - 1
max_value = (2 ** p) - 1
random_lut = np.random.randint(lower_bound, upper_bound, size=2**p)
itype = get_lut_integer_type(p)
print(f"description: unsigned_signed_apply_lookup_table_{p}bits")
print("program: |")
print(
f" func.func @main(%arg0: !FHE.eint<{p}>) -> !FHE.esint<{p}> {{")
print(f" %tlu = arith.constant dense<[{','.join(map(str, random_lut))}]> : tensor<{2**p}xi64>")
f" func.func @main(%arg0: !FHE.eint<{p}>, %arg1: tensor<{2**p}x{itype}>) -> !FHE.esint<{p}> {{")
print(
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %tlu): (!FHE.eint<{p}>, tensor<{2**p}xi64>) -> (!FHE.esint<{p}>)")
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %arg1): (!FHE.eint<{p}>, tensor<{2**p}x{itype}>) -> (!FHE.esint<{p}>)")
print(f" return %1: !FHE.esint<{p}>")
print(" }")
if p >= PRECISION_FORCE_CRT:
@@ -65,17 +84,26 @@ def generate(args):
print(" - inputs:")
random_i = np.random.randint(max_value)
print(f" - scalar: {random_i}")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[random_i]}")
print(f" signed: true")
if not args.minimal:
print(" - inputs:")
print(" - scalar: 0")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[0]}")
print(f" signed: true")
print(" - inputs:")
print(f" - scalar: {max_value}")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[max_value]}")
print(f" signed: true")
@@ -85,13 +113,14 @@ def generate(args):
lower_bound = -(2 ** (p-1))
upper_bound = (2 ** (p-1)) - 1
random_lut = np.random.randint(lower_bound, upper_bound, size=2**p)
itype = get_lut_integer_type(p)
print(f"description: signed_apply_lookup_table_{p}bits")
print("program: |")
print(
f" func.func @main(%arg0: !FHE.esint<{p}>) -> !FHE.esint<{p}> {{")
print(f" %tlu = arith.constant dense<[{','.join(map(str, random_lut))}]> : tensor<{2**p}xi64>")
f" func.func @main(%arg0: !FHE.esint<{p}>, %arg1: tensor<{2**p}x{itype}>) -> !FHE.esint<{p}> {{")
print(
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %tlu): (!FHE.esint<{p}>, tensor<{2**p}xi64>) -> (!FHE.esint<{p}>)")
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %arg1): (!FHE.esint<{p}>, tensor<{2**p}x{itype}>) -> (!FHE.esint<{p}>)")
print(f" return %1: !FHE.esint<{p}>")
print(" }")
if p >= PRECISION_FORCE_CRT:
@@ -102,6 +131,9 @@ def generate(args):
random_i = np.random.randint(lower_bound, upper_bound)
print(f" - scalar: {random_i}")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[random_i]}")
print(f" signed: true")
@@ -109,24 +141,36 @@ def generate(args):
print(" - inputs:")
print(f" - scalar: 0")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[0]}")
print(f" signed: true")
print(" - inputs:")
print(f" - scalar: {upper_bound}")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[upper_bound]}")
print(f" signed: true")
print(" - inputs:")
print(f" - scalar: {lower_bound}")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[lower_bound]}")
print(f" signed: true")
print(" - inputs:")
print(f" - scalar: -1")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(f" signed: true")
print(" outputs:")
print(f" - scalar: {random_lut[-1]}")
print(f" signed: true")
@@ -138,13 +182,13 @@ def generate(args):
upper_bound = (2 ** (p-1)) - 1
max_value = (2 ** p) - 1
random_lut = np.random.randint(max_value+1, size=2**p)
itype = get_lut_integer_type(p)
print(f"description: signed_unsigned_apply_lookup_table_{p}bits")
print("program: |")
print(
f" func.func @main(%arg0: !FHE.esint<{p}>) -> !FHE.eint<{p}> {{")
print(f" %tlu = arith.constant dense<[{','.join(map(str, random_lut))}]> : tensor<{2**p}xi64>")
f" func.func @main(%arg0: !FHE.esint<{p}>, %arg1: tensor<{2**p}x{itype}>) -> !FHE.eint<{p}> {{")
print(
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %tlu): (!FHE.esint<{p}>, tensor<{2**p}xi64>) -> (!FHE.eint<{p}>)")
f" %1 = \"FHE.apply_lookup_table\"(%arg0, %arg1): (!FHE.esint<{p}>, tensor<{2**p}x{itype}>) -> (!FHE.eint<{p}>)")
print(f" return %1: !FHE.eint<{p}>")
print(" }")
if p >= PRECISION_FORCE_CRT:
@@ -155,27 +199,37 @@ def generate(args):
random_i = np.random.randint(lower_bound, upper_bound)
print(f" - scalar: {random_i}")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[random_i]}")
if not args.minimal:
print(" - inputs:")
print(f" - scalar: 0")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[0]}")
print(" - inputs:")
print(f" - scalar: {upper_bound}")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[upper_bound]}")
print(" - inputs:")
print(f" - scalar: {lower_bound}")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[lower_bound]}")
print(" - inputs:")
print(f" - scalar: -1")
print(f" signed: true")
print(f" - tensor: [{','.join(map(str, random_lut))}]")
print(f" shape: [{2**p}]")
print(" outputs:")
print(f" - scalar: {random_lut[-1]}")
print("---")