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Add adjoint hessian called tfq.math.inner_product_hessian #530

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Add adjoint hessian called tfq.math.inner_product_hessian #530

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2ba9d73
Fix adjoint hessian bug
jaeyoo Apr 2, 2021
018e541
Add analytic diff on PhasedXPowGate
jaeyoo Apr 2, 2021
0079d53
Fix the adjoint hessian bug and add ComputeSmall
jaeyoo Apr 3, 2021
1c3f25c
Add inner_product_hessian import_test
jaeyoo Apr 3, 2021
2e44e03
Fix lint
jaeyoo Apr 3, 2021
2a12594
Fix format
jaeyoo Apr 3, 2021
67a16f9
Fix format
jaeyoo Apr 3, 2021
0141262
Fix timeout by reducing the number of symbols
jaeyoo Apr 3, 2021
5f6ffcd
Fix test inputs
jaeyoo Apr 3, 2021
4e01d1d
Fix name
jaeyoo Apr 3, 2021
acea17b
Fix typo
jaeyoo Apr 3, 2021
1789108
Add mutex in ComputeSmall
jaeyoo Apr 3, 2021
c53a754
Merge branch 'master' into inner_prod_hessian_wo_phased_x_pow_gate
jaeyoo Apr 4, 2021
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1 change: 1 addition & 0 deletions scripts/import_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,6 +36,7 @@ def test_imports():

# Math ops.
_ = tfq.math.inner_product
_ = tfq.math.inner_product_hessian

# Noisy simulation ops.
_ = tfq.noise.expectation
Expand Down
12 changes: 12 additions & 0 deletions tensorflow_quantum/core/ops/math_ops/BUILD
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Expand Up @@ -17,6 +17,7 @@ cc_binary(
srcs = [
"tfq_inner_product.cc",
"tfq_inner_product_grad.cc",
"tfq_inner_product_hessian.cc",
],
copts = select({
":windows": [
Expand Down Expand Up @@ -62,6 +63,7 @@ cc_binary(
# cirq cc proto
"//tensorflow_quantum/core/ops:parse_context",
"//tensorflow_quantum/core/ops:tfq_simulate_utils",
"//tensorflow_quantum/core/src:adj_hessian_util",
"//tensorflow_quantum/core/src:adj_util",
"//tensorflow_quantum/core/src:circuit_parser_qsim",
"//tensorflow_quantum/core/src:util_qsim",
Expand Down Expand Up @@ -100,3 +102,13 @@ py_test(
"//tensorflow_quantum/python:util",
],
)

py_test(
name = "inner_product_hessian_test",
srcs = ["inner_product_hessian_test.py"],
python_version = "PY3",
deps = [
":inner_product_op_py",
"//tensorflow_quantum/python:util",
],
)
3 changes: 2 additions & 1 deletion tensorflow_quantum/core/ops/math_ops/__init__.py
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Expand Up @@ -14,4 +14,5 @@
# ==============================================================================
"""Module for tfq.core.ops.math_ops.*"""

from tensorflow_quantum.core.ops.math_ops.inner_product_op import inner_product
from tensorflow_quantum.core.ops.math_ops.inner_product_op import (
inner_product, inner_product_hessian)
10 changes: 5 additions & 5 deletions tensorflow_quantum/core/ops/math_ops/inner_product_grad_test.py
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Expand Up @@ -27,7 +27,7 @@ class InnerProductAdjGradTest(tf.test.TestCase, parameterized.TestCase):
"""Tests tfq_inner_product_grad."""

def test_inner_product_grad_inputs(self):
"""Makes sure that inner_product_adj_grad fails on bad inputs."""
"""Makes sure that inner_product_grad fails on bad inputs."""
n_qubits = 5
batch_size = 5
n_other_programs = 3
Expand Down Expand Up @@ -232,7 +232,7 @@ def test_inner_product_grad_inputs(self):
])
def test_correctness_with_symbols(self, n_qubits, batch_size,
inner_dim_size):
"""Tests that inner_product works with symbols."""
"""Tests that inner_product_grad works with symbols."""
symbol_names = ['alpha', 'beta', 'gamma']
n_params = len(symbol_names)
qubits = cirq.GridQubit.rect(1, n_qubits)
Expand All @@ -242,7 +242,7 @@ def test_correctness_with_symbols(self, n_qubits, batch_size,

other_batch = [
util.random_circuit_resolver_batch(qubits, inner_dim_size)[0]
for i in range(batch_size)
for _ in range(batch_size)
]

symbol_values_array = np.array(
Expand Down Expand Up @@ -312,15 +312,15 @@ def test_correctness_with_symbols(self, n_qubits, batch_size,
])
def test_correctness_without_symbols(self, n_qubits, batch_size,
inner_dim_size):
"""Tests that inner_product_adj_grad works without symbols."""
"""Tests that inner_product_grad works without symbols."""
qubits = cirq.GridQubit.rect(1, n_qubits)
circuit_batch, _ = \
util.random_circuit_resolver_batch(
qubits, batch_size)

other_batch = [
util.random_circuit_resolver_batch(qubits, inner_dim_size)[0]
for i in range(batch_size)
for _ in range(batch_size)
]

programs = util.convert_to_tensor(circuit_batch)
Expand Down
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