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test: add tests of np.dot with compile_numpy_function_into_op_graph

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closes #201
This commit is contained in:
Benoit Chevallier-Mames
2021-08-25 15:58:23 +02:00
committed by Benoit Chevallier
parent 1ebbd3ea91
commit 9a3e15e89a
1 changed files with 54 additions and 5 deletions
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59
tests/hnumpy/test_compile.py
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@@ -8,7 +8,7 @@ import pytest
from hdk.common.data_types.integers import Integer
from hdk.common.debugging import draw_graph, get_printable_graph
from hdk.common.extensions.table import LookupTable
from hdk.common.values import EncryptedValue
from hdk.common.values import EncryptedTensor, EncryptedValue
from hdk.hnumpy.compile import (
compile_numpy_function,
compile_numpy_function_into_op_graph,
@@ -43,7 +43,7 @@ def no_fuse_unhandled(x, y):
],
)
def test_compile_function_multiple_outputs(function, input_ranges, list_of_arg_names):
"""Test function compile_numpy_function for a program with multiple outputs"""
"""Test function compile_numpy_function_into_op_graph for a program with multiple outputs"""
def data_gen(args):
for prod in itertools.product(*args):
@@ -131,7 +131,7 @@ def test_compile_and_run_correctness(function, input_ranges, list_of_arg_names):
def test_compile_function_with_direct_tlu():
"""Test compile_numpy_function for a program with direct table lookup"""
"""Test compile_numpy_function_into_op_graph for a program with direct table lookup"""
table = LookupTable([9, 2, 4, 11])
@@ -149,7 +149,7 @@ def test_compile_function_with_direct_tlu():
def test_compile_function_with_direct_tlu_overflow():
"""Test compile_numpy_function for a program with direct table lookup overflow"""
"""Test compile_numpy_function_into_op_graph for a program with direct table lookup overflow"""
table = LookupTable([9, 2, 4, 11])
@@ -171,7 +171,7 @@ def test_compile_function_with_direct_tlu_overflow():
],
)
def test_fail_compile(function, input_ranges, list_of_arg_names):
"""Test function compile_numpy_function for a program with signed values"""
"""Test function compile_numpy_function_into_op_graph for a program with signed values"""
def data_gen(args):
for prod in itertools.product(*args):
@@ -187,3 +187,52 @@ def test_fail_compile(function, input_ranges, list_of_arg_names):
function_parameters,
data_gen(tuple(range(x[0], x[1] + 1) for x in input_ranges)),
)
@pytest.mark.parametrize(
"function,params,shape,ref_graph_str",
[
# pylint: disable=unnecessary-lambda
(
lambda x, y: numpy.dot(x, y),
{
"x": EncryptedTensor(Integer(2, is_signed=False), shape=(4,)),
"y": EncryptedTensor(Integer(2, is_signed=False), shape=(4,)),
},
(4,),
# Remark that, when you do the dot of tensors of 4 values between 0 and 3,
# you can get a maximal value of 4*3*3 = 36, ie something on 6 bits
"\n%0 = x # Integer<unsigned, 2 bits>"
"\n%1 = y # Integer<unsigned, 2 bits>"
"\n%2 = Dot(0, 1) # Integer<unsigned, 6 bits>"
"\nreturn(%2)",
),
# pylint: enable=unnecessary-lambda
],
)
def test_compile_function_with_dot(function, params, shape, ref_graph_str):
"""Test compile_numpy_function_into_op_graph for a program with np.dot"""
# This is the exhaust, but if ever we have too long inputs (ie, large 'repeat'),
# we'll have to take random values, not all values one by one
def data_gen(max_for_ij, repeat):
iter_i = itertools.product(range(0, max_for_ij + 1), repeat=repeat)
iter_j = itertools.product(range(0, max_for_ij + 1), repeat=repeat)
for prod_i, prod_j in itertools.product(iter_i, iter_j):
yield (prod_i, prod_j)
max_for_ij = 3
assert len(shape) == 1
repeat = shape[0]
op_graph = compile_numpy_function_into_op_graph(
function,
params,
data_gen(max_for_ij, repeat),
)
str_of_the_graph = get_printable_graph(op_graph, show_data_types=True)
assert str_of_the_graph == ref_graph_str, (
f"\n==================\nGot {str_of_the_graph}"
f"\n==================\nExpected {ref_graph_str}"
f"\n==================\n"
)