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fix(benchmarks): resolve simple errors in some of the benchmarks

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This commit is contained in:
Umut
2021-11-18 17:26:53 +03:00
parent 4c6e1661ec
commit efde01258c
74 changed files with 156 additions and 135 deletions
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3
benchmarks/124_minus_x.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -36,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/124_minus_x_tensor.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 6, size=(3,))
sample_x = np.random.randint(0, 2 ** 6, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/c_concatenate_x.py
View File

@@ -18,7 +18,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -38,7 +38,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

10
benchmarks/c_matmul_x.py
View File

@@ -7,19 +7,19 @@ import concrete.numpy as hnp
def main():
c = np.arange(20, 30).reshape((5, 2))
c = np.arange(1, 7).reshape((3, 2))
def function_to_compile(x):
return np.matmul(c, x)
x = hnp.EncryptedTensor(hnp.UnsignedInteger(3), shape=(2, 4))
x = hnp.EncryptedTensor(hnp.UnsignedInteger(2), shape=(2, 3))
inputset = [(np.random.randint(0, 2 ** 3, size=(2, 4))) for _ in range(128)]
inputset = [(np.random.randint(0, 2 ** 2, size=(2, 3)),) for _ in range(128)]
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(2, 4))
sample_x = np.random.randint(0, 2 ** 2, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -39,7 +39,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/multi_table_lookup.py
View File

@@ -38,7 +38,7 @@ def main():
inputs = []
labels = []
for _ in range(50):
sample_x = np.random.randint(0, 2 ** input_bits, size=(3, 2))
sample_x = np.random.randint(0, 2 ** input_bits, size=(3, 2), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -49,7 +49,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/single_table_lookup.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -41,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x-index-0-and-0.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(3, 2))
sample_x = np.random.randint(0, 2 ** 3, size=(3, 2), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x-index-0.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x-index-1.py
View File

@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x-index-colon-2.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x-index-colon-and-1.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(3, 2))
sample_x = np.random.randint(0, 2 ** 3, size=(3, 2), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x-index-colon.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x-index-minus-1.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x-index-one-colon.py
View File

@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x-reversed.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_concatenate_c.py
View File

@@ -18,7 +18,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -38,7 +38,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_concatenate_y.py
View File

@@ -21,8 +21,8 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5))
sample_y = np.random.randint(0, 2 ** 3, size=(4, 5))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5), dtype=np.uint8)
sample_y = np.random.randint(0, 2 ** 3, size=(4, 5), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -42,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_index_colon_and_y_clear.py
View File

@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_index_colon_and_y_encrypted.py
View File

@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_colon_colon_minus_1_and_y_and_z_clear.py
View File

@@ -37,7 +37,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(5, 4, 2))
sample_x = np.random.randint(0, 2 ** 3, size=(5, 4, 2), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
sample_z = random.randint(0, (2 ** 1) - 1)
@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_index_colon_colon_minus_1_and_y_and_z_encrypted.py
View File

@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_index_y_and_1_colon_clear.py
View File

@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_y_and_1_colon_encrypted.py
View File

@@ -32,7 +32,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
inputs.append([sample_x, sample_y])
@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_index_y_and_colon_and_z_clear.py
View File

@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_y_and_colon_and_z_encrypted.py
View File

@@ -37,7 +37,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5, 2))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 5, 2), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
sample_z = random.randint(0, (2 ** 1) - 1)
@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_y_and_colon_clear.py
View File

@@ -32,7 +32,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
inputs.append([sample_x, sample_y])
@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_y_and_colon_encrypted.py
View File

@@ -32,7 +32,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
inputs.append([sample_x, sample_y])
@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_index_y_and_z_and_0_clear.py
View File

@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_y_and_z_and_0_encrypted.py
View File

@@ -37,7 +37,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2, 5))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2, 5), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
sample_z = random.randint(0, (2 ** 1) - 1)
@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_index_y_and_z_clear.py
View File

@@ -18,7 +18,7 @@ def main():
inputset = [
(
np.random.randint(0, 2 ** 3, size=(4, 2)),
np.random.randint(0, 2 ** 3, size=(4, 2), dtype=np.uint8),
random.randint(0, (2 ** 2) - 1),
random.randint(0, (2 ** 1) - 1),
)
@@ -37,7 +37,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2))
sample_x = np.random.randint(0, 2 ** 3, size=(4, 2), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
sample_z = random.randint(0, (2 ** 1) - 1)
@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_index_y_and_z_encrypted.py
View File

@@ -50,7 +50,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_y_clear.py
View File

@@ -32,7 +32,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4,))
sample_x = np.random.randint(0, 2 ** 3, size=(4,), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
inputs.append([sample_x, sample_y])
@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_index_y_encrypted.py
View File

@@ -32,7 +32,7 @@ def main():
inputs = []
labels = []
for _ in range(100):
sample_x = np.random.randint(0, 2 ** 3, size=(4,))
sample_x = np.random.randint(0, 2 ** 3, size=(4,), dtype=np.uint8)
sample_y = random.randint(0, (2 ** 2) - 1)
inputs.append([sample_x, sample_y])
@@ -44,7 +44,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

10
benchmarks/x_matmul_c.py
View File

@@ -7,19 +7,19 @@ import concrete.numpy as hnp
def main():
c = np.arange(20).reshape((4, 5))
c = np.arange(6).reshape((3, 2))
def function_to_compile(x):
return np.matmul(x, c)
x = hnp.EncryptedTensor(hnp.UnsignedInteger(3), shape=(2, 4))
x = hnp.EncryptedTensor(hnp.UnsignedInteger(2), shape=(2, 3))
inputset = [(np.random.randint(0, 2 ** 3, size=(2, 4))) for _ in range(128)]
inputset = [(np.random.randint(0, 2 ** 2, size=(2, 3)),) for _ in range(128)]
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(2, 4))
sample_x = np.random.randint(0, 2 ** 2, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -39,7 +39,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

12
benchmarks/x_matmul_y.py
View File

@@ -10,19 +10,19 @@ def main():
def function_to_compile(x, y):
return np.matmul(x, y)
x = hnp.EncryptedTensor(hnp.UnsignedInteger(3), shape=(2, 4))
y = hnp.EncryptedTensor(hnp.UnsignedInteger(3), shape=(4, 5))
x = hnp.EncryptedTensor(hnp.UnsignedInteger(2), shape=(2, 3))
y = hnp.EncryptedTensor(hnp.UnsignedInteger(2), shape=(3, 2))
inputset = [
(np.random.randint(0, 2 ** 3, size=(2, 4)), np.random.randint(0, 2 ** 3, size=(4, 5)))
(np.random.randint(0, 2 ** 2, size=(2, 3)), np.random.randint(0, 2 ** 2, size=(3, 2)))
for _ in range(128)
]
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(2, 4))
sample_y = np.random.randint(0, 2 ** 3, size=(4, 5))
sample_x = np.random.randint(0, 2 ** 2, size=(2, 3), dtype=np.uint8)
sample_y = np.random.randint(0, 2 ** 2, size=(3, 2), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -42,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_minus_1_2_3.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(3, 2 ** 3, size=(3,))
sample_x = np.random.randint(3, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_minus_1_2_3_broadcasted.py
View File

@@ -28,7 +28,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(3, 2 ** 3, size=(2, 3))
sample_x = np.random.randint(3, 2 ** 3, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -39,7 +39,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_minus_24.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -36,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_minus_24_tensor.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(24, 2 ** 6, size=(3,))
sample_x = np.random.randint(24, 2 ** 6, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_minus_y.py
View File

@@ -3,6 +3,7 @@
import itertools
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -41,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_minus_y_broadcasted_tensors.py
View File

@@ -30,8 +30,8 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(4, 2 ** 3, size=(3,))
sample_y = np.random.randint(0, 5, size=(2, 3))
sample_x = np.random.randint(4, 2 ** 3, size=(3,), dtype=np.uint8)
sample_y = np.random.randint(0, 5, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -42,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_minus_y_tensor_and_scalar.py
View File

@@ -41,7 +41,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_minus_y_tensors.py
View File

@@ -29,8 +29,8 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(3, 2 ** 3, size=(3,))
sample_y = np.random.randint(0, 4, size=(3,))
sample_x = np.random.randint(3, 2 ** 3, size=(3,), dtype=np.uint8)
sample_y = np.random.randint(0, 4, size=(3,), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -41,7 +41,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_negative.py
View File

@@ -17,7 +17,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(10, 6))
sample_x = np.random.randint(0, 2 ** 3, size=(10, 6), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_plus_1_2_3.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_plus_1_2_3_broadcasted.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(2, 3))
sample_x = np.random.randint(0, 2 ** 3, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -36,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_10b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_11b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_12b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_13b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_14b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_15b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_16b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_32b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_8b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_42_9b.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -39,7 +40,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_plus_42_tensor.py
View File

@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_plus_y.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -38,7 +39,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_plus_y_broadcasted_tensors.py
View File

@@ -30,8 +30,8 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_y = np.random.randint(0, 2 ** 3, size=(2, 3))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
sample_y = np.random.randint(0, 2 ** 3, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -42,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_plus_y_tensor_and_scalar.py
View File

@@ -29,7 +29,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
sample_y = random.randint(0, 2 ** 3 - 1)
inputs.append([sample_x, sample_y])
@@ -41,7 +41,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_plus_y_tensors.py
View File

@@ -30,8 +30,8 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_y = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
sample_y = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -42,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_reshape.py
View File

@@ -17,7 +17,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(10, 6))
sample_x = np.random.randint(0, 2 ** 3, size=(10, 6), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_times_1_2_3.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_times_1_2_3_broadcasted.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(2, 3))
sample_x = np.random.randint(0, 2 ** 3, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_times_7.py
View File

@@ -2,6 +2,7 @@
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -36,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_times_7_tensor.py
View File

@@ -26,7 +26,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

3
benchmarks/x_times_y.py
View File

@@ -3,6 +3,7 @@
import itertools
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -41,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_times_y_broadcasted_tensors.py
View File

@@ -30,8 +30,8 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_y = np.random.randint(0, 2 ** 3, size=(2, 3))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
sample_y = np.random.randint(0, 2 ** 3, size=(2, 3), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -42,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

2
benchmarks/x_times_y_tensor_and_scalar.py
View File

@@ -41,7 +41,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

6
benchmarks/x_times_y_tensors.py
View File

@@ -30,8 +30,8 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(3,))
sample_y = np.random.randint(0, 2 ** 3, size=(3,))
sample_x = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
sample_y = np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8)
inputs.append([sample_x, sample_y])
labels.append(function_to_compile(*inputs[-1]))
@@ -42,7 +42,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

5
benchmarks/x_to_the_power_of_2.py
View File

@@ -1,7 +1,8 @@
# bench: Unit Target: x**2
# bench: Unit Target: x ** 2
import random
import numpy as np
from common import BENCHMARK_CONFIGURATION
import concrete.numpy as hnp
@@ -36,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
benchmarks/x_tranpose.py
View File

@@ -17,7 +17,7 @@ def main():
inputs = []
labels = []
for _ in range(4):
sample_x = np.random.randint(0, 2 ** 3, size=(2, 4))
sample_x = np.random.randint(0, 2 ** 3, size=(2, 4), dtype=np.uint8)
inputs.append([sample_x])
labels.append(function_to_compile(*inputs[-1]))
@@ -37,7 +37,7 @@ def main():
result_i = engine.run(*input_i)
# bench: Measure: End
if result_i == label_i:
if np.array_equal(result_i, label_i):
correct += 1
# bench: Measure: Accuracy (%) = (correct / len(inputs)) * 100

4
script/progress_tracker_utils/measure.py
View File

@@ -14,7 +14,7 @@ def name_to_id(name):
"""Convert a human readable name to a url friendly id (e.g., `x + y` to `x-plus-y`)"""
name = name.replace("-", "minus")
name = name.replace("**", "-to-the-power-of-")
name = name.replace(" ** ", "-to-the-power-of-")
name = name.replace("+", "plus")
name = name.replace("*", "times")
name = name.replace("/", "over")
@@ -24,6 +24,8 @@ def name_to_id(name):
name = name.replace(" ", "-")
name = name.replace("(", "")
name = name.replace(")", "")
name = name.replace("[", "")
name = name.replace("]", "")
name = name.replace(",", "")
name = name.replace(".", "-")