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tensor: Fix dimensions for fp16 in script

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This commit is contained in:
Hansung Kim
2024-08-12 15:20:27 -07:00
parent c1906ebb4f
commit 07dd9e35a0
2 changed files with 25 additions and 20 deletions
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25
tests/kernel/tensor/check_correctness.py
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@@ -41,9 +41,13 @@ def C_index(threadgroup, thread, register):
def check_sim_output():
file = input("simulator output filename: ")
A_array = np.zeros((16, 8))
B_array = np.zeros((8, 16))
C_array = np.zeros((16, 16))
M = 8
N = 8
K = 16
A_array = np.zeros((M, K))
B_array = np.zeros((K, N))
C_array = np.zeros((M, N))
with open(file) as f:
for line in f.readlines():
@@ -87,26 +91,23 @@ def check_sim_output():
if __name__ == "__main__":
expected = np.load("abc.npz")
# expected_A = expected['A_array']
# expected_B = expected['B_array']
# expected_C = expected['C_array']
expected_A = expected['A_array'][0:8, 0:8]
expected_B = expected['B_array'][0:8, 0:8]
expected_C = expected['C_array'][0:8, 0:8]
expected_A = expected['A_array']
expected_B = expected['B_array']
expected_C = expected['C_array']
expected_C = expected_C + expected_A @ expected_B
print('expected A:')
print(expected_A)
print('expected B:')
print(expected_B)
print('expected C:')
print(expected_C[0:8, 0:8])
print(expected_C)
expected_C.astype('float32').tofile("c_expected.bin")
[got_A, got_B, got_C] = check_sim_output()
print('got C:')
print(C_array[0:8, 0:8])
print(C_array)
print('diff C:')
print(expected_C[0:8, 0:8] - C_array[0:8, 0:8])
print(expected_C - C_array)
assert np.allclose(expected_A, got_A)
assert np.allclose(expected_B, got_B)
assert np.allclose(expected_C, got_C)

20
tests/kernel/tensor/generate_matrix.py
View File

@@ -1,10 +1,14 @@
import numpy as np
M = 8
N = 8
K = 16
# A_array = np.random.rand(8, 16)
A_array = np.arange(8 * 8).reshape([8, 8])
B_array = np.arange(8 * 8).reshape([8, 8])
A_array = np.arange(M * K).reshape([M, K])
B_array = np.arange(K * N).reshape([K, N])
# C_array = np.random.rand(16, 16)
C_array = np.zeros([8, 8])
C_array = np.zeros([M, N])
# A_array = np.zeros((16, 8))
# B_array = np.zeros((8, 16))
# A_array[0,:] = 1.0
@@ -56,10 +60,10 @@ if __name__ == "__main__":
np.savez("abc", A_array=A_array, B_array=B_array, C_array=C_array)
A_array.astype('float32').tofile("input.a.bin")
B_array.astype('float32').tofile("input.b.bin")
# A_array.astype('float32').tofile("input.a.bin")
# B_array.astype('float32').tofile("input.b.bin")
# A_array.astype('float16').tofile("input.a.bin")
# B_array = pack_fp16_by_column(B_array)
# B_array.astype('float16').tofile("input.b.bin")
A_array.astype('float16').tofile("input.a.bin")
B_array = pack_fp16_by_column(B_array)
B_array.astype('float16').tofile("input.b.bin")
print(B_array)