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def test(name, lhs, rhs, equation, output, lhs_data, rhs_data, output_data):
model = Model().Operation("EINSUM_EX", lhs, rhs, equation).To(output)
example = Example({
lhs: lhs_data,
rhs: rhs_data,
output: output_data,
}, model=model, name=name)
test(
name = 'matmul_2x2_2',
lhs = Input("input0", "TENSOR_FLOAT32", "{2, 3}"),
rhs = Input("input1", "TENSOR_FLOAT32", "{3, 2}"),
equation = Parameter("eq", "TENSOR_QUANT8_ASYMM", "{9}, 1.0, 0",
[105, 107, 44, 107, 106, 45, 62, 105, 106]), # ik,kj->ij
lhs_data=[0., 1., 2., 3., 4., 5.],
rhs_data=[0., 3., 1., 4., 2., 5.],
output=Output("output0", "TENSOR_FLOAT32", "{2, 2}"),
output_data=[5., 14., 14., 50.]
)
# abc,cde->abde
dim_a = 2
dim_b = 2
dim_c = 4
dim_d = 3
dim_e = 3
lhs_value = [x for x in range(dim_a * dim_b * dim_c)]
rhs_value = [x for x in range(dim_c * dim_d * dim_e)]
result_value = [0 for x in range(dim_a * dim_b * dim_d * dim_e)]
for a in range(dim_a):
for b in range(dim_b):
for d in range(dim_d):
for e in range(dim_e):
result_index = e + dim_e * (d + dim_d * (b + dim_b * a))
for c in range(dim_c):
lhs_index = c + dim_c * (b + dim_b * a)
rhs_index = e + dim_e * (d + dim_d * c)
result_value[result_index] = result_value[result_index] + lhs_value[lhs_index] * rhs_value[rhs_index]
test(
name = 'matmul_3x3_4',
lhs = Input("input0", "TENSOR_FLOAT32", "{2, 2, 4}"),
rhs = Input("input1", "TENSOR_FLOAT32", "{4, 3, 3}"),
equation = Parameter("eq", "TENSOR_QUANT8_ASYMM", "{13}, 1.0, 0",
[97, 98, 99, 44, 99, 100, 101, 45, 62, 97, 98, 100, 101]), # abc,cde->abde
lhs_data=lhs_value,
rhs_data=rhs_value,
output=Output("output0", "TENSOR_FLOAT32", "{2, 2, 3, 3}"),
output_data=result_value
)
# abc,cd->abd
dim_a = 2
dim_b = 3
dim_c = 4
dim_d = 3
lhs_value = [x for x in range(dim_a * dim_b * dim_c)]
rhs_value = [x for x in range(dim_c * dim_d)]
result_value = [0 for x in range(dim_a * dim_b * dim_d)]
for a in range(dim_a):
for b in range(dim_b):
for d in range(dim_d):
result_index = d + dim_d * (b + dim_b * a)
for c in range(dim_c):
lhs_index = c + dim_c * (b + dim_b * a)
rhs_index = d + dim_d * c
result_value[result_index] = result_value[result_index] + lhs_value[lhs_index] * rhs_value[rhs_index]
test(
name = 'matmul_3x2_3',
lhs = Input("input0", "TENSOR_FLOAT32", "{2, 3, 4}"),
rhs = Input("input1", "TENSOR_FLOAT32", "{4, 3}"),
equation = Parameter("eq", "TENSOR_QUANT8_ASYMM", "{11}, 1.0, 0",
[97, 98, 99, 44, 99, 100, 45, 62, 97, 98, 100]), # abc,cd->abd
lhs_data=lhs_value,
rhs_data=rhs_value,
output=Output("output0", "TENSOR_FLOAT32", "{2, 3, 3}"),
output_data=result_value
)
# abcd,adbe->acbe
dim_a = 2
dim_b = 3
dim_c = 4
dim_d = 2
dim_e = 4
lhs_value = [x for x in range(dim_a * dim_b * dim_c * dim_d)]
rhs_value = [x for x in range(dim_a * dim_d * dim_b * dim_e)]
result_value = [0 for x in range(dim_a * dim_c * dim_b * dim_e)]
for a in range(dim_a):
for c in range(dim_c):
for b in range(dim_b):
for e in range(dim_e):
result_index = e + dim_e * (b + dim_b * (c + dim_c * a))
for d in range(dim_d):
lhs_index = d + dim_d * (c + dim_c * (b + dim_b * a))
rhs_index = e + dim_e * (b + dim_b * (d + dim_d * a))
result_value[result_index] = result_value[result_index] + lhs_value[lhs_index] * rhs_value[rhs_index]
test(
name = 'matmul_4x4_4',
lhs = Input("input0", "TENSOR_FLOAT32", "{2, 3, 4, 2}"),
rhs = Input("input1", "TENSOR_FLOAT32", "{2, 2, 3, 4}"),
equation = Parameter("eq", "TENSOR_QUANT8_ASYMM", "{15}, 1.0, 0",
[97, 98, 99, 100, 44, 97, 100, 98, 101, 45, 62, 97, 99, 98, 101]), # abcd,adbe->acbe
lhs_data=lhs_value,
rhs_data=rhs_value,
output=Output("output0", "TENSOR_FLOAT32", "{2, 4, 3, 4}"),
output_data=result_value
)
# abcd,aecd->aceb
dim_a = 2
dim_b = 3
dim_c = 2
dim_d = 4
dim_e = 3
lhs_value = [x for x in range(dim_a * dim_b * dim_c * dim_d)]
rhs_value = [x for x in range(dim_a * dim_e * dim_c * dim_d)]
result_value = [0 for x in range(dim_a * dim_c * dim_e * dim_b)]
for a in range(dim_a):
for c in range(dim_c):
for b in range(dim_e):
for e in range(dim_b):
result_index = b + dim_b * (e + dim_e * (c + dim_c * a))
for d in range(dim_d):
lhs_index = d + dim_d * (c + dim_c * (b + dim_b * a))
rhs_index = d + dim_d * (c + dim_c * (e + dim_e * a))
result_value[result_index] = result_value[result_index] + lhs_value[lhs_index] * rhs_value[rhs_index]
test(
name = 'matmul_4x4_4_2',
lhs = Input("input0", "TENSOR_FLOAT32", "{2, 3, 2, 4}"),
rhs = Input("input1", "TENSOR_FLOAT32", "{2, 3, 2, 4}"),
equation = Parameter("eq", "TENSOR_QUANT8_ASYMM", "{15}, 1.0, 0",
[97, 98, 99, 100, 44, 97, 101, 99, 100, 45, 62, 97, 99, 101, 98]), # abcd,aecd->aceb
lhs_data=lhs_value,
rhs_data=rhs_value,
output=Output("output0", "TENSOR_FLOAT32", "{2, 2, 3, 3}"),
output_data=result_value
)
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