repo stringlengths 7 54 | path stringlengths 4 223 | func_name stringlengths 1 134 | original_string stringlengths 75 104k | language stringclasses 1
value | code stringlengths 75 104k | code_tokens listlengths 20 28.4k | docstring stringlengths 1 46.3k | docstring_tokens listlengths 1 1.66k | sha stringlengths 40 40 | url stringlengths 87 315 | partition stringclasses 1
value | summary stringlengths 4 350 | obf_code stringlengths 7.85k 764k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | GLUnpickler.persistent_load | def persistent_load(self, pid):
"""
Reconstruct a GLC object using the persistent ID.
This method should not be used externally. It is required by the unpickler super class.
Parameters
----------
pid : The persistent ID used in pickle file to save the GLC object.
... | python | def persistent_load(self, pid):
"""
Reconstruct a GLC object using the persistent ID.
This method should not be used externally. It is required by the unpickler super class.
Parameters
----------
pid : The persistent ID used in pickle file to save the GLC object.
... | [
"def",
"persistent_load",
"(",
"self",
",",
"pid",
")",
":",
"if",
"len",
"(",
"pid",
")",
"==",
"2",
":",
"# Pre GLC-1.3 release behavior, without memorization",
"type_tag",
",",
"filename",
"=",
"pid",
"abs_path",
"=",
"_os",
".",
"path",
".",
"join",
"(",... | Reconstruct a GLC object using the persistent ID.
This method should not be used externally. It is required by the unpickler super class.
Parameters
----------
pid : The persistent ID used in pickle file to save the GLC object.
Returns
----------
The GLC o... | [
"Reconstruct",
"a",
"GLC",
"object",
"using",
"the",
"persistent",
"ID",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/_gl_pickle.py#L472-L500 | train | Reconstruct a GLC object using the persistent ID. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | GLUnpickler.close | def close(self):
"""
Clean up files that were created.
"""
if self.file:
self.file.close()
self.file = None
# If temp_file is a folder, we do not remove it because we may
# still need it after the unpickler is disposed
if self.tmp_file and... | python | def close(self):
"""
Clean up files that were created.
"""
if self.file:
self.file.close()
self.file = None
# If temp_file is a folder, we do not remove it because we may
# still need it after the unpickler is disposed
if self.tmp_file and... | [
"def",
"close",
"(",
"self",
")",
":",
"if",
"self",
".",
"file",
":",
"self",
".",
"file",
".",
"close",
"(",
")",
"self",
".",
"file",
"=",
"None",
"# If temp_file is a folder, we do not remove it because we may",
"# still need it after the unpickler is disposed",
... | Clean up files that were created. | [
"Clean",
"up",
"files",
"that",
"were",
"created",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/_gl_pickle.py#L502-L514 | train | Clean up files that were created. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_converter.py | convert | def convert(sk_obj, input_features = None,
output_feature_names = None):
"""
Convert scikit-learn pipeline, classifier, or regressor to Core ML format.
Parameters
----------
sk_obj: model | [model] of scikit-learn format.
Scikit learn model(s) to convert to a Core ML format.
... | python | def convert(sk_obj, input_features = None,
output_feature_names = None):
"""
Convert scikit-learn pipeline, classifier, or regressor to Core ML format.
Parameters
----------
sk_obj: model | [model] of scikit-learn format.
Scikit learn model(s) to convert to a Core ML format.
... | [
"def",
"convert",
"(",
"sk_obj",
",",
"input_features",
"=",
"None",
",",
"output_feature_names",
"=",
"None",
")",
":",
"# This function is just a thin wrapper around the internal converter so",
"# that sklearn isn't actually imported unless this function is called",
"from",
".",
... | Convert scikit-learn pipeline, classifier, or regressor to Core ML format.
Parameters
----------
sk_obj: model | [model] of scikit-learn format.
Scikit learn model(s) to convert to a Core ML format.
The input model may be a single scikit learn model, a scikit learn
pipeline model, ... | [
"Convert",
"scikit",
"-",
"learn",
"pipeline",
"classifier",
"or",
"regressor",
"to",
"Core",
"ML",
"format",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_converter.py#L10-L148 | train | Convert a single or many scikit - learn model or regressor into a Core ML format. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/reflection.py | ParseMessage | def ParseMessage(descriptor, byte_str):
"""Generate a new Message instance from this Descriptor and a byte string.
Args:
descriptor: Protobuf Descriptor object
byte_str: Serialized protocol buffer byte string
Returns:
Newly created protobuf Message object.
"""
result_class = MakeClass(descriptor... | python | def ParseMessage(descriptor, byte_str):
"""Generate a new Message instance from this Descriptor and a byte string.
Args:
descriptor: Protobuf Descriptor object
byte_str: Serialized protocol buffer byte string
Returns:
Newly created protobuf Message object.
"""
result_class = MakeClass(descriptor... | [
"def",
"ParseMessage",
"(",
"descriptor",
",",
"byte_str",
")",
":",
"result_class",
"=",
"MakeClass",
"(",
"descriptor",
")",
"new_msg",
"=",
"result_class",
"(",
")",
"new_msg",
".",
"ParseFromString",
"(",
"byte_str",
")",
"return",
"new_msg"
] | Generate a new Message instance from this Descriptor and a byte string.
Args:
descriptor: Protobuf Descriptor object
byte_str: Serialized protocol buffer byte string
Returns:
Newly created protobuf Message object. | [
"Generate",
"a",
"new",
"Message",
"instance",
"from",
"this",
"Descriptor",
"and",
"a",
"byte",
"string",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/reflection.py#L67-L80 | train | Parse a new Message from this Descriptor and a byte string. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/reflection.py | MakeClass | def MakeClass(descriptor):
"""Construct a class object for a protobuf described by descriptor.
Composite descriptors are handled by defining the new class as a member of the
parent class, recursing as deep as necessary.
This is the dynamic equivalent to:
class Parent(message.Message):
__metaclass__ = Ge... | python | def MakeClass(descriptor):
"""Construct a class object for a protobuf described by descriptor.
Composite descriptors are handled by defining the new class as a member of the
parent class, recursing as deep as necessary.
This is the dynamic equivalent to:
class Parent(message.Message):
__metaclass__ = Ge... | [
"def",
"MakeClass",
"(",
"descriptor",
")",
":",
"if",
"descriptor",
"in",
"MESSAGE_CLASS_CACHE",
":",
"return",
"MESSAGE_CLASS_CACHE",
"[",
"descriptor",
"]",
"attributes",
"=",
"{",
"}",
"for",
"name",
",",
"nested_type",
"in",
"descriptor",
".",
"nested_types... | Construct a class object for a protobuf described by descriptor.
Composite descriptors are handled by defining the new class as a member of the
parent class, recursing as deep as necessary.
This is the dynamic equivalent to:
class Parent(message.Message):
__metaclass__ = GeneratedProtocolMessageType
D... | [
"Construct",
"a",
"class",
"object",
"for",
"a",
"protobuf",
"described",
"by",
"descriptor",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/reflection.py#L83-L121 | train | Constructs a class object for a protobuf described by descriptor. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _convert_1bit_array_to_byte_array | def _convert_1bit_array_to_byte_array(arr):
"""
Convert bit array to byte array.
:param arr: list
Bits as a list where each element is an integer of 0 or 1
Returns
-------
numpy.array
1D numpy array of type uint8
"""
# Padding if necessary
while len(arr) < 8 or len(... | python | def _convert_1bit_array_to_byte_array(arr):
"""
Convert bit array to byte array.
:param arr: list
Bits as a list where each element is an integer of 0 or 1
Returns
-------
numpy.array
1D numpy array of type uint8
"""
# Padding if necessary
while len(arr) < 8 or len(... | [
"def",
"_convert_1bit_array_to_byte_array",
"(",
"arr",
")",
":",
"# Padding if necessary",
"while",
"len",
"(",
"arr",
")",
"<",
"8",
"or",
"len",
"(",
"arr",
")",
"%",
"8",
":",
"arr",
".",
"append",
"(",
"0",
")",
"arr",
"=",
"_np",
".",
"array",
... | Convert bit array to byte array.
:param arr: list
Bits as a list where each element is an integer of 0 or 1
Returns
-------
numpy.array
1D numpy array of type uint8 | [
"Convert",
"bit",
"array",
"to",
"byte",
"array",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L34-L65 | train | Convert 1bit array to byte array. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _decompose_bytes_to_bit_arr | def _decompose_bytes_to_bit_arr(arr):
"""
Unpack bytes to bits
:param arr: list
Byte Stream, as a list of uint8 values
Returns
-------
bit_arr: list
Decomposed bit stream as a list of 0/1s of length (len(arr) * 8)
"""
bit_arr = []
for idx in range(len(arr)):
... | python | def _decompose_bytes_to_bit_arr(arr):
"""
Unpack bytes to bits
:param arr: list
Byte Stream, as a list of uint8 values
Returns
-------
bit_arr: list
Decomposed bit stream as a list of 0/1s of length (len(arr) * 8)
"""
bit_arr = []
for idx in range(len(arr)):
... | [
"def",
"_decompose_bytes_to_bit_arr",
"(",
"arr",
")",
":",
"bit_arr",
"=",
"[",
"]",
"for",
"idx",
"in",
"range",
"(",
"len",
"(",
"arr",
")",
")",
":",
"for",
"i",
"in",
"reversed",
"(",
"range",
"(",
"8",
")",
")",
":",
"bit_arr",
".",
"append",... | Unpack bytes to bits
:param arr: list
Byte Stream, as a list of uint8 values
Returns
-------
bit_arr: list
Decomposed bit stream as a list of 0/1s of length (len(arr) * 8) | [
"Unpack",
"bytes",
"to",
"bits"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L77-L93 | train | Unpacks a byte stream to a list of bits. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _get_linear_lookup_table_and_weight | def _get_linear_lookup_table_and_weight(nbits, wp):
"""
Generate a linear lookup table.
:param nbits: int
Number of bits to represent a quantized weight value
:param wp: numpy.array
Weight blob to be quantized
Returns
-------
lookup_table: numpy.array
Lookup table ... | python | def _get_linear_lookup_table_and_weight(nbits, wp):
"""
Generate a linear lookup table.
:param nbits: int
Number of bits to represent a quantized weight value
:param wp: numpy.array
Weight blob to be quantized
Returns
-------
lookup_table: numpy.array
Lookup table ... | [
"def",
"_get_linear_lookup_table_and_weight",
"(",
"nbits",
",",
"wp",
")",
":",
"w",
"=",
"wp",
".",
"reshape",
"(",
"1",
",",
"-",
"1",
")",
"qw",
",",
"scales",
",",
"biases",
"=",
"_quantize_channelwise_linear",
"(",
"w",
",",
"nbits",
",",
"axis",
... | Generate a linear lookup table.
:param nbits: int
Number of bits to represent a quantized weight value
:param wp: numpy.array
Weight blob to be quantized
Returns
-------
lookup_table: numpy.array
Lookup table of shape (2^nbits, )
qw: numpy.array
Decomposed bit ... | [
"Generate",
"a",
"linear",
"lookup",
"table",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L96-L117 | train | Generates a linear lookup table. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _get_kmeans_lookup_table_and_weight | def _get_kmeans_lookup_table_and_weight(nbits, w, init='k-means++', tol=1e-2, n_init=1, rand_seed=0):
"""
Generate K-Means lookup table given a weight parameter field
:param nbits:
Number of bits for quantization
:param w:
Weight as numpy array
Returns
-------
lut: numpy.a... | python | def _get_kmeans_lookup_table_and_weight(nbits, w, init='k-means++', tol=1e-2, n_init=1, rand_seed=0):
"""
Generate K-Means lookup table given a weight parameter field
:param nbits:
Number of bits for quantization
:param w:
Weight as numpy array
Returns
-------
lut: numpy.a... | [
"def",
"_get_kmeans_lookup_table_and_weight",
"(",
"nbits",
",",
"w",
",",
"init",
"=",
"'k-means++'",
",",
"tol",
"=",
"1e-2",
",",
"n_init",
"=",
"1",
",",
"rand_seed",
"=",
"0",
")",
":",
"if",
"_HAS_SKLEARN",
":",
"from",
"sklearn",
".",
"cluster",
"... | Generate K-Means lookup table given a weight parameter field
:param nbits:
Number of bits for quantization
:param w:
Weight as numpy array
Returns
-------
lut: numpy.array
Lookup table, numpy array of shape (1 << nbits, );
wq: numpy.array
Quantized weight of ty... | [
"Generate",
"K",
"-",
"Means",
"lookup",
"table",
"given",
"a",
"weight",
"parameter",
"field"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L120-L149 | train | Generate a K - Means lookup table given a weight parameter field. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _quantize_channelwise_linear | def _quantize_channelwise_linear(weight, nbits, axis=0):
"""
Linearly quantize weight blob.
:param weight: numpy.array
Weight to be quantized.
:param nbits: int
Number of bits per weight element
:param axis: int
Axis of the weight blob to compute channel-wise quantization,... | python | def _quantize_channelwise_linear(weight, nbits, axis=0):
"""
Linearly quantize weight blob.
:param weight: numpy.array
Weight to be quantized.
:param nbits: int
Number of bits per weight element
:param axis: int
Axis of the weight blob to compute channel-wise quantization,... | [
"def",
"_quantize_channelwise_linear",
"(",
"weight",
",",
"nbits",
",",
"axis",
"=",
"0",
")",
":",
"if",
"len",
"(",
"weight",
".",
"shape",
")",
"==",
"1",
":",
"# vector situation, treat as 1 channel",
"weight",
"=",
"weight",
".",
"reshape",
"(",
"(",
... | Linearly quantize weight blob.
:param weight: numpy.array
Weight to be quantized.
:param nbits: int
Number of bits per weight element
:param axis: int
Axis of the weight blob to compute channel-wise quantization, can be 0 or 1
Returns
-------
quantized_weight: numpy.a... | [
"Linearly",
"quantize",
"weight",
"blob",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L151-L212 | train | Linearly quantize a weight blob. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _quantize_wp | def _quantize_wp(wp, nbits, qm, axis=0, **kwargs):
"""
Quantize the weight blob
:param wp: numpy.array
Weight parameters
:param nbits: int
Number of bits
:param qm:
Quantization mode
:param lut_function: (``callable function``)
Python callable representing a look... | python | def _quantize_wp(wp, nbits, qm, axis=0, **kwargs):
"""
Quantize the weight blob
:param wp: numpy.array
Weight parameters
:param nbits: int
Number of bits
:param qm:
Quantization mode
:param lut_function: (``callable function``)
Python callable representing a look... | [
"def",
"_quantize_wp",
"(",
"wp",
",",
"nbits",
",",
"qm",
",",
"axis",
"=",
"0",
",",
"*",
"*",
"kwargs",
")",
":",
"scale",
"=",
"bias",
"=",
"lut",
"=",
"None",
"# Linear Quantization",
"if",
"qm",
"==",
"_QUANTIZATION_MODE_LINEAR_QUANTIZATION",
":",
... | Quantize the weight blob
:param wp: numpy.array
Weight parameters
:param nbits: int
Number of bits
:param qm:
Quantization mode
:param lut_function: (``callable function``)
Python callable representing a look-up table
Returns
-------
scale: numpy.array
... | [
"Quantize",
"the",
"weight",
"blob"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L215-L266 | train | Quantize the weight blob of nbits bits as a single array of nbits. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _quantize_wp_field | def _quantize_wp_field(wp, nbits, qm, shape, axis=0, **kwargs):
"""
Quantize WeightParam field in Neural Network Protobuf
:param wp: MLModel.NeuralNetwork.WeightParam
WeightParam field
:param nbits: int
Number of bits to be quantized
:param qm: str
Quantization mode
:pa... | python | def _quantize_wp_field(wp, nbits, qm, shape, axis=0, **kwargs):
"""
Quantize WeightParam field in Neural Network Protobuf
:param wp: MLModel.NeuralNetwork.WeightParam
WeightParam field
:param nbits: int
Number of bits to be quantized
:param qm: str
Quantization mode
:pa... | [
"def",
"_quantize_wp_field",
"(",
"wp",
",",
"nbits",
",",
"qm",
",",
"shape",
",",
"axis",
"=",
"0",
",",
"*",
"*",
"kwargs",
")",
":",
"# De-quantization",
"if",
"qm",
"==",
"_QUANTIZATION_MODE_DEQUANTIZE",
":",
"return",
"_dequantize_wp",
"(",
"wp",
","... | Quantize WeightParam field in Neural Network Protobuf
:param wp: MLModel.NeuralNetwork.WeightParam
WeightParam field
:param nbits: int
Number of bits to be quantized
:param qm: str
Quantization mode
:param shape: tuple
Tensor shape held by wp
:param axis: int
... | [
"Quantize",
"WeightParam",
"field",
"in",
"Neural",
"Network",
"Protobuf"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L269-L336 | train | Quantize WeightParam field in Neural Network protobuf. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | compare_models | def compare_models(full_precision_model, quantized_model,
sample_data):
"""
Utility function to compare the performance of a full precision vs quantized model
:param full_precision_model: MLModel
The full precision model with float32 weights
:param quantized_model... | python | def compare_models(full_precision_model, quantized_model,
sample_data):
"""
Utility function to compare the performance of a full precision vs quantized model
:param full_precision_model: MLModel
The full precision model with float32 weights
:param quantized_model... | [
"def",
"compare_models",
"(",
"full_precision_model",
",",
"quantized_model",
",",
"sample_data",
")",
":",
"emessage",
"=",
"(",
"\"\"\"\n Invalid sample data provided. Only a list of dictionaries\n containing sample data or path to a folder containing images is\n supported\"\"\"... | Utility function to compare the performance of a full precision vs quantized model
:param full_precision_model: MLModel
The full precision model with float32 weights
:param quantized_model: MLModel
Quantized version of the model with quantized weights
:param sample_data: str | [dict]
... | [
"Utility",
"function",
"to",
"compare",
"the",
"performance",
"of",
"a",
"full",
"precision",
"vs",
"quantized",
"model"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L829-L874 | train | Utility function to compare the performance of a full precision vs a quantized model with a list of sample data. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | quantize_weights | def quantize_weights(full_precision_model,
nbits,
quantization_mode="linear",
sample_data=None,
**kwargs):
"""
Utility function to convert a full precision (float) MLModel to a
nbit quantized MLModel (float16).
:param f... | python | def quantize_weights(full_precision_model,
nbits,
quantization_mode="linear",
sample_data=None,
**kwargs):
"""
Utility function to convert a full precision (float) MLModel to a
nbit quantized MLModel (float16).
:param f... | [
"def",
"quantize_weights",
"(",
"full_precision_model",
",",
"nbits",
",",
"quantization_mode",
"=",
"\"linear\"",
",",
"sample_data",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"qmode_mapping",
"=",
"{",
"\"linear\"",
":",
"_QUANTIZATION_MODE_LINEAR_QUANTIZATI... | Utility function to convert a full precision (float) MLModel to a
nbit quantized MLModel (float16).
:param full_precision_model: MLModel
Model which will be converted to half precision. Currently conversion
for only neural network models is supported. If a pipeline model is
passed in th... | [
"Utility",
"function",
"to",
"convert",
"a",
"full",
"precision",
"(",
"float",
")",
"MLModel",
"to",
"a",
"nbit",
"quantized",
"MLModel",
"(",
"float16",
")",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py#L877-L977 | train | Utility function to characterize the weights of a single neural network model in a base - 2 nbit - quantized MLModel. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/item_similarity_recommender.py | create | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
nearest_items=None,
similarity_type='jaccard',
threshold=0.001,
only_top_k=64,
verbose=True,
target_memory_usage = 8*102... | python | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
nearest_items=None,
similarity_type='jaccard',
threshold=0.001,
only_top_k=64,
verbose=True,
target_memory_usage = 8*102... | [
"def",
"create",
"(",
"observation_data",
",",
"user_id",
"=",
"'user_id'",
",",
"item_id",
"=",
"'item_id'",
",",
"target",
"=",
"None",
",",
"user_data",
"=",
"None",
",",
"item_data",
"=",
"None",
",",
"nearest_items",
"=",
"None",
",",
"similarity_type",... | Create a recommender that uses item-item similarities based on
users in common.
Parameters
----------
observation_data : SFrame
The dataset to use for training the model. It must contain a column of
user ids and a column of item ids. Each row represents an observed
interaction b... | [
"Create",
"a",
"recommender",
"that",
"uses",
"item",
"-",
"item",
"similarities",
"based",
"on",
"users",
"in",
"common",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/item_similarity_recommender.py#L17-L259 | train | Creates a new recommender that uses item - item similarities based on the given observations. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | _get_elementwise_name_from_keras_layer | def _get_elementwise_name_from_keras_layer(keras_layer):
"""
Get the keras layer name from the activation name.
"""
if isinstance(keras_layer, _keras.layers.Add):
return 'ADD'
elif isinstance(keras_layer, _keras.layers.Multiply):
return 'MULTIPLY'
elif isinstance(keras_layer, _ke... | python | def _get_elementwise_name_from_keras_layer(keras_layer):
"""
Get the keras layer name from the activation name.
"""
if isinstance(keras_layer, _keras.layers.Add):
return 'ADD'
elif isinstance(keras_layer, _keras.layers.Multiply):
return 'MULTIPLY'
elif isinstance(keras_layer, _ke... | [
"def",
"_get_elementwise_name_from_keras_layer",
"(",
"keras_layer",
")",
":",
"if",
"isinstance",
"(",
"keras_layer",
",",
"_keras",
".",
"layers",
".",
"Add",
")",
":",
"return",
"'ADD'",
"elif",
"isinstance",
"(",
"keras_layer",
",",
"_keras",
".",
"layers",
... | Get the keras layer name from the activation name. | [
"Get",
"the",
"keras",
"layer",
"name",
"from",
"the",
"activation",
"name",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L76-L117 | train | Get the elementwise name from the keras layer. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_dense | def convert_dense(builder, layer, input_names, output_names, keras_layer):
"""
Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and o... | python | def convert_dense(builder, layer, input_names, output_names, keras_layer):
"""
Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and o... | [
"def",
"convert_dense",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",
"0",
... | Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"a",
"dense",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L137-L165 | train | Convert a dense layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_embedding | def convert_embedding(builder, layer, input_names, output_names, keras_layer):
"""Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and ou... | python | def convert_embedding(builder, layer, input_names, output_names, keras_layer):
"""Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and ou... | [
"def",
"convert_embedding",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",
"... | Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"a",
"dense",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L167-L192 | train | Convert a dense layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_activation | def convert_activation(builder, layer, input_names, output_names, keras_layer):
"""
Convert an activation layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get ... | python | def convert_activation(builder, layer, input_names, output_names, keras_layer):
"""
Convert an activation layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get ... | [
"def",
"convert_activation",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",
... | Convert an activation layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"an",
"activation",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L194-L267 | train | Convert an activation layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_advanced_relu | def convert_advanced_relu(builder, layer, input_names, output_names, keras_layer):
"""
Convert an ReLU layer with maximum value from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
... | python | def convert_advanced_relu(builder, layer, input_names, output_names, keras_layer):
"""
Convert an ReLU layer with maximum value from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
... | [
"def",
"convert_advanced_relu",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",... | Convert an ReLU layer with maximum value from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"an",
"ReLU",
"layer",
"with",
"maximum",
"value",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L269-L302 | train | Convert an advanced RELU layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_convolution | def convert_convolution(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check... | python | def convert_convolution(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check... | [
"def",
"convert_convolution",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"_check_data_format",
"(",
"keras_layer",
")",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",... | Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"convolution",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L304-L383 | train | Convert a convolution layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_convolution1d | def convert_convolution1d(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get... | python | def convert_convolution1d(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get... | [
"def",
"convert_convolution1d",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",... | Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"convolution",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L386-L449 | train | Convert a convolution layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_separable_convolution | def convert_separable_convolution(builder, layer, input_names, output_names, keras_layer):
"""
Convert separable convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.... | python | def convert_separable_convolution(builder, layer, input_names, output_names, keras_layer):
"""
Convert separable convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.... | [
"def",
"convert_separable_convolution",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"_check_data_format",
"(",
"keras_layer",
")",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"inp... | Convert separable convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"separable",
"convolution",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L451-L529 | train | Convert a separable convolution layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_batchnorm | def convert_batchnorm(builder, layer, input_names, output_names, keras_layer):
"""
Convert a Batch Normalization layer.
Parameters
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and output names
i... | python | def convert_batchnorm(builder, layer, input_names, output_names, keras_layer):
"""
Convert a Batch Normalization layer.
Parameters
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and output names
i... | [
"def",
"convert_batchnorm",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",
"... | Convert a Batch Normalization layer.
Parameters
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"a",
"Batch",
"Normalization",
"layer",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L531-L581 | train | Convert a Batch Normalization layer from keras to Neural Network. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_flatten | def convert_flatten(builder, layer, input_names, output_names, keras_layer):
"""
Convert a flatten layer from keras to coreml.
----------
Parameters
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
input_name, ou... | python | def convert_flatten(builder, layer, input_names, output_names, keras_layer):
"""
Convert a flatten layer from keras to coreml.
----------
Parameters
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
input_name, ou... | [
"def",
"convert_flatten",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",
"0",
"]",
")",
"# blob_order ==... | Convert a flatten layer from keras to coreml.
----------
Parameters
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"a",
"flatten",
"layer",
"from",
"keras",
"to",
"coreml",
".",
"----------",
"Parameters",
"keras_layer",
":",
"layer",
"A",
"keras",
"layer",
"object",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L584-L619 | train | Convert a flatten layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_merge | def convert_merge(builder, layer, input_names, output_names, keras_layer):
"""
Convert concat layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and ou... | python | def convert_merge(builder, layer, input_names, output_names, keras_layer):
"""
Convert concat layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and ou... | [
"def",
"convert_merge",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"output_name",
"=",
"output_names",
"[",
"0",
"]",
"mode",
"=",
"_get_elementwise_name_from_keras_layer",
"(",
... | Convert concat layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"concat",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L621-L638 | train | Convert concat layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_pooling | def convert_pooling(builder, layer, input_names, output_names, keras_layer):
"""
Convert pooling layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check_data_for... | python | def convert_pooling(builder, layer, input_names, output_names, keras_layer):
"""
Convert pooling layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check_data_for... | [
"def",
"convert_pooling",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"_check_data_format",
"(",
"keras_layer",
")",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"... | Convert pooling layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"pooling",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L640-L729 | train | Convert a pooling layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_padding | def convert_padding(builder, layer, input_names, output_names, keras_layer):
"""
Convert padding layer from keras to coreml.
Keras only supports zero padding at this time.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural n... | python | def convert_padding(builder, layer, input_names, output_names, keras_layer):
"""
Convert padding layer from keras to coreml.
Keras only supports zero padding at this time.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural n... | [
"def",
"convert_padding",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"_check_data_format",
"(",
"keras_layer",
")",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"... | Convert padding layer from keras to coreml.
Keras only supports zero padding at this time.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"padding",
"layer",
"from",
"keras",
"to",
"coreml",
".",
"Keras",
"only",
"supports",
"zero",
"padding",
"at",
"this",
"time",
".",
"Parameters",
"----------",
"keras_layer",
":",
"layer",
"A",
"keras",
"layer",
"object",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L731-L782 | train | Convert a padding layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_cropping | def convert_cropping(builder, layer, input_names, output_names, keras_layer):
"""
Convert padding layer from keras to coreml.
Keras only supports zero padding at this time.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural ... | python | def convert_cropping(builder, layer, input_names, output_names, keras_layer):
"""
Convert padding layer from keras to coreml.
Keras only supports zero padding at this time.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural ... | [
"def",
"convert_cropping",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"_check_data_format",
"(",
"keras_layer",
")",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
... | Convert padding layer from keras to coreml.
Keras only supports zero padding at this time.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"padding",
"layer",
"from",
"keras",
"to",
"coreml",
".",
"Keras",
"only",
"supports",
"zero",
"padding",
"at",
"this",
"time",
".",
"Parameters",
"----------",
"keras_layer",
":",
"layer",
"A",
"keras",
"layer",
"object",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L784-L835 | train | Convert a cropping layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_upsample | def convert_upsample(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check_dat... | python | def convert_upsample(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check_dat... | [
"def",
"convert_upsample",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"_check_data_format",
"(",
"keras_layer",
")",
"# Get input and output names",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
... | Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"convolution",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L837-L880 | train | Convert a upsample layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_permute | def convert_permute(builder, layer, input_names, output_names, keras_layer):
"""
Convert a softmax layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
input_name, o... | python | def convert_permute(builder, layer, input_names, output_names, keras_layer):
"""
Convert a softmax layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
input_name, o... | [
"def",
"convert_permute",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"input_name",
",",
"output_name",
"=",
"(",
"input_names",
"[",
"0",
"]",
",",
"output_names",
"[",
"0",
"]",
")",
"keras_dims",
... | Convert a softmax layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"a",
"softmax",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L882-L916 | train | Convert a permute layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_simple_rnn | def convert_simple_rnn(builder, layer, input_names, output_names, keras_layer):
"""
Convert an SimpleRNN layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get i... | python | def convert_simple_rnn(builder, layer, input_names, output_names, keras_layer):
"""
Convert an SimpleRNN layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get i... | [
"def",
"convert_simple_rnn",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"# Get input and output names",
"hidden_size",
"=",
"keras_layer",
".",
"units",
"input_size",
"=",
"keras_layer",
".",
"input_shape",
"... | Convert an SimpleRNN layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"an",
"SimpleRNN",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L951-L995 | train | Convert a SimpleRNN layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_lstm | def convert_lstm(builder, layer, input_names, output_names, keras_layer):
"""
Convert an LSTM layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
hidden_size = ker... | python | def convert_lstm(builder, layer, input_names, output_names, keras_layer):
"""
Convert an LSTM layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
hidden_size = ker... | [
"def",
"convert_lstm",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"hidden_size",
"=",
"keras_layer",
".",
"units",
"input_size",
"=",
"keras_layer",
".",
"input_shape",
"[",
"-",
"1",
"]",
"output_all",... | Convert an LSTM layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"an",
"LSTM",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L997-L1055 | train | Convert an LSTM layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_gru | def convert_gru(builder, layer, input_names, output_names, keras_layer):
"""
Convert a GRU layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
hidden_size = keras_... | python | def convert_gru(builder, layer, input_names, output_names, keras_layer):
"""
Convert a GRU layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
hidden_size = keras_... | [
"def",
"convert_gru",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"hidden_size",
"=",
"keras_layer",
".",
"units",
"input_size",
"=",
"keras_layer",
".",
"input_shape",
"[",
"-",
"1",
"]",
"output_all",
... | Convert a GRU layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"a",
"GRU",
"layer",
"from",
"keras",
"to",
"coreml",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L1057-L1112 | train | Convert a GRU layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_bidirectional | def convert_bidirectional(builder, layer, input_names, output_names, keras_layer):
"""
Convert a bidirectional layer from keras to coreml.
Currently assumes the units are LSTMs.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A n... | python | def convert_bidirectional(builder, layer, input_names, output_names, keras_layer):
"""
Convert a bidirectional layer from keras to coreml.
Currently assumes the units are LSTMs.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A n... | [
"def",
"convert_bidirectional",
"(",
"builder",
",",
"layer",
",",
"input_names",
",",
"output_names",
",",
"keras_layer",
")",
":",
"input_size",
"=",
"keras_layer",
".",
"input_shape",
"[",
"-",
"1",
"]",
"lstm_layer",
"=",
"keras_layer",
".",
"forward_layer",... | Convert a bidirectional layer from keras to coreml.
Currently assumes the units are LSTMs.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
"Convert",
"a",
"bidirectional",
"layer",
"from",
"keras",
"to",
"coreml",
".",
"Currently",
"assumes",
"the",
"units",
"are",
"LSTMs",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py#L1114-L1232 | train | Convert a bidirectional layer from keras to coreml. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/meta/decompiler/simple_instructions.py | SimpleInstructions.SLICE_0 | def SLICE_0(self, instr):
'obj[:]'
value = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=None, step=None, upper=None, **kw)
subscr = _ast.Subscript(value=value, slice=slice, ctx=_ast.Load(), **kw)
self.ast_stack.append(subscr... | python | def SLICE_0(self, instr):
'obj[:]'
value = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=None, step=None, upper=None, **kw)
subscr = _ast.Subscript(value=value, slice=slice, ctx=_ast.Load(), **kw)
self.ast_stack.append(subscr... | [
"def",
"SLICE_0",
"(",
"self",
",",
"instr",
")",
":",
"value",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
"kw",
"=",
"dict",
"(",
"lineno",
"=",
"instr",
".",
"lineno",
",",
"col_offset",
"=",
"0",
")",
"slice",
"=",
"_ast",
".",
"Slic... | obj[:] | [
"obj",
"[",
":",
"]"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/meta/decompiler/simple_instructions.py#L723-L731 | train | Slice instruction. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/meta/decompiler/simple_instructions.py | SimpleInstructions.STORE_SLICE_1 | def STORE_SLICE_1(self, instr):
'obj[lower:] = expr'
lower = self.ast_stack.pop()
value = self.ast_stack.pop()
expr = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=lower, step=None, upper=None, **kw)
subscr = _ast.Subs... | python | def STORE_SLICE_1(self, instr):
'obj[lower:] = expr'
lower = self.ast_stack.pop()
value = self.ast_stack.pop()
expr = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=lower, step=None, upper=None, **kw)
subscr = _ast.Subs... | [
"def",
"STORE_SLICE_1",
"(",
"self",
",",
"instr",
")",
":",
"lower",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
"value",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
"expr",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
... | obj[lower:] = expr | [
"obj",
"[",
"lower",
":",
"]",
"=",
"expr"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/meta/decompiler/simple_instructions.py#L802-L813 | train | Store_SLICE_1 is an ast. Store_SLICE_1 instruction. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/meta/decompiler/simple_instructions.py | SimpleInstructions.STORE_SLICE_3 | def STORE_SLICE_3(self, instr):
'obj[lower:upper] = expr'
upper = self.ast_stack.pop()
lower = self.ast_stack.pop()
value = self.ast_stack.pop()
expr = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=lower, step... | python | def STORE_SLICE_3(self, instr):
'obj[lower:upper] = expr'
upper = self.ast_stack.pop()
lower = self.ast_stack.pop()
value = self.ast_stack.pop()
expr = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=lower, step... | [
"def",
"STORE_SLICE_3",
"(",
"self",
",",
"instr",
")",
":",
"upper",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
"lower",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
"value",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
... | obj[lower:upper] = expr | [
"obj",
"[",
"lower",
":",
"upper",
"]",
"=",
"expr"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/meta/decompiler/simple_instructions.py#L829-L849 | train | STORE_SLICE_3 - Store a set of keys in the current stack. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/meta/decompiler/simple_instructions.py | SimpleInstructions.DELETE_SLICE_0 | def DELETE_SLICE_0(self, instr):
'obj[:] = expr'
value = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=None, step=None, upper=None, **kw)
subscr = _ast.Subscript(value=value, slice=slice, ctx=_ast.Del(), **kw)
delete = _ast.D... | python | def DELETE_SLICE_0(self, instr):
'obj[:] = expr'
value = self.ast_stack.pop()
kw = dict(lineno=instr.lineno, col_offset=0)
slice = _ast.Slice(lower=None, step=None, upper=None, **kw)
subscr = _ast.Subscript(value=value, slice=slice, ctx=_ast.Del(), **kw)
delete = _ast.D... | [
"def",
"DELETE_SLICE_0",
"(",
"self",
",",
"instr",
")",
":",
"value",
"=",
"self",
".",
"ast_stack",
".",
"pop",
"(",
")",
"kw",
"=",
"dict",
"(",
"lineno",
"=",
"instr",
".",
"lineno",
",",
"col_offset",
"=",
"0",
")",
"slice",
"=",
"_ast",
".",
... | obj[:] = expr | [
"obj",
"[",
":",
"]",
"=",
"expr"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/meta/decompiler/simple_instructions.py#L851-L860 | train | Delete SLICE_0 instruction. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/item_content_recommender.py | create | def create(item_data, item_id,
observation_data = None,
user_id = None, target = None,
weights = 'auto',
similarity_metrics = 'auto',
item_data_transform = 'auto',
max_item_neighborhood_size = 64, verbose=True):
"""Create a content-based recommender... | python | def create(item_data, item_id,
observation_data = None,
user_id = None, target = None,
weights = 'auto',
similarity_metrics = 'auto',
item_data_transform = 'auto',
max_item_neighborhood_size = 64, verbose=True):
"""Create a content-based recommender... | [
"def",
"create",
"(",
"item_data",
",",
"item_id",
",",
"observation_data",
"=",
"None",
",",
"user_id",
"=",
"None",
",",
"target",
"=",
"None",
",",
"weights",
"=",
"'auto'",
",",
"similarity_metrics",
"=",
"'auto'",
",",
"item_data_transform",
"=",
"'auto... | Create a content-based recommender model in which the similarity
between the items recommended is determined by the content of
those items rather than learned from user interaction data.
The similarity score between two items is calculated by first
computing the similarity between the item data for eac... | [
"Create",
"a",
"content",
"-",
"based",
"recommender",
"model",
"in",
"which",
"the",
"similarity",
"between",
"the",
"items",
"recommended",
"is",
"determined",
"by",
"the",
"content",
"of",
"those",
"items",
"rather",
"than",
"learned",
"from",
"user",
"inte... | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/item_content_recommender.py#L20-L255 | train | Create a content - based recommender model for the items in the item_data. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/meta/asttools/visitors/cond_symbol_visitor.py | lhs | def lhs(node):
'''
Return a set of symbols in `node` that are assigned.
:param node: ast node
:returns: set of strings.
'''
gen = ConditionalSymbolVisitor()
if isinstance(node, (list, tuple)):
gen.visit_list(node)
else:
gen.visit(node)
return gen.lhs | python | def lhs(node):
'''
Return a set of symbols in `node` that are assigned.
:param node: ast node
:returns: set of strings.
'''
gen = ConditionalSymbolVisitor()
if isinstance(node, (list, tuple)):
gen.visit_list(node)
else:
gen.visit(node)
return gen.lhs | [
"def",
"lhs",
"(",
"node",
")",
":",
"gen",
"=",
"ConditionalSymbolVisitor",
"(",
")",
"if",
"isinstance",
"(",
"node",
",",
"(",
"list",
",",
"tuple",
")",
")",
":",
"gen",
".",
"visit_list",
"(",
"node",
")",
"else",
":",
"gen",
".",
"visit",
"("... | Return a set of symbols in `node` that are assigned.
:param node: ast node
:returns: set of strings. | [
"Return",
"a",
"set",
"of",
"symbols",
"in",
"node",
"that",
"are",
"assigned",
".",
":",
"param",
"node",
":",
"ast",
"node",
":",
"returns",
":",
"set",
"of",
"strings",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/meta/asttools/visitors/cond_symbol_visitor.py#L363-L377 | train | Return a set of symbols in node that are assigned. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/meta/asttools/visitors/cond_symbol_visitor.py | conditional_lhs | def conditional_lhs(node):
'''
Group outputs into conditional and stable
:param node: ast node
:returns: tuple of (conditional, stable)
'''
gen = ConditionalSymbolVisitor()
gen.visit(node)
return gen.cond_lhs, gen.stable_lhs | python | def conditional_lhs(node):
'''
Group outputs into conditional and stable
:param node: ast node
:returns: tuple of (conditional, stable)
'''
gen = ConditionalSymbolVisitor()
gen.visit(node)
return gen.cond_lhs, gen.stable_lhs | [
"def",
"conditional_lhs",
"(",
"node",
")",
":",
"gen",
"=",
"ConditionalSymbolVisitor",
"(",
")",
"gen",
".",
"visit",
"(",
"node",
")",
"return",
"gen",
".",
"cond_lhs",
",",
"gen",
".",
"stable_lhs"
] | Group outputs into conditional and stable
:param node: ast node
:returns: tuple of (conditional, stable) | [
"Group",
"outputs",
"into",
"conditional",
"and",
"stable",
":",
"param",
"node",
":",
"ast",
"node",
":",
"returns",
":",
"tuple",
"of",
"(",
"conditional",
"stable",
")"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/meta/asttools/visitors/cond_symbol_visitor.py#L395-L406 | train | Group outputs into conditional and stable
| Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/meta/asttools/visitors/cond_symbol_visitor.py | conditional_symbols | def conditional_symbols(node):
'''
Group lhs and rhs into conditional, stable and undefined
:param node: ast node
:returns: tuple of (conditional_lhs, stable_lhs),(conditional_rhs, stable_rhs), undefined
'''
gen = ConditionalSymbolVisitor()
gen.visit(node)
lhs = gen.cond_lhs,... | python | def conditional_symbols(node):
'''
Group lhs and rhs into conditional, stable and undefined
:param node: ast node
:returns: tuple of (conditional_lhs, stable_lhs),(conditional_rhs, stable_rhs), undefined
'''
gen = ConditionalSymbolVisitor()
gen.visit(node)
lhs = gen.cond_lhs,... | [
"def",
"conditional_symbols",
"(",
"node",
")",
":",
"gen",
"=",
"ConditionalSymbolVisitor",
"(",
")",
"gen",
".",
"visit",
"(",
"node",
")",
"lhs",
"=",
"gen",
".",
"cond_lhs",
",",
"gen",
".",
"stable_lhs",
"rhs",
"=",
"gen",
".",
"cond_rhs",
",",
"g... | Group lhs and rhs into conditional, stable and undefined
:param node: ast node
:returns: tuple of (conditional_lhs, stable_lhs),(conditional_rhs, stable_rhs), undefined | [
"Group",
"lhs",
"and",
"rhs",
"into",
"conditional",
"stable",
"and",
"undefined",
":",
"param",
"node",
":",
"ast",
"node",
":",
"returns",
":",
"tuple",
"of",
"(",
"conditional_lhs",
"stable_lhs",
")",
"(",
"conditional_rhs",
"stable_rhs",
")",
"undefined"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/meta/asttools/visitors/cond_symbol_visitor.py#L409-L423 | train | Group lhs rhs into conditional stable and undefined
| Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/xgboost/subtree/rabit/wrapper/rabit.py | _loadlib | def _loadlib(lib='standard'):
"""Load rabit library."""
global _LIB
if _LIB is not None:
warnings.warn('rabit.int call was ignored because it has'\
' already been initialized', level=2)
return
if lib == 'standard':
_LIB = ctypes.cdll.LoadLibrary(WRAPPER_... | python | def _loadlib(lib='standard'):
"""Load rabit library."""
global _LIB
if _LIB is not None:
warnings.warn('rabit.int call was ignored because it has'\
' already been initialized', level=2)
return
if lib == 'standard':
_LIB = ctypes.cdll.LoadLibrary(WRAPPER_... | [
"def",
"_loadlib",
"(",
"lib",
"=",
"'standard'",
")",
":",
"global",
"_LIB",
"if",
"_LIB",
"is",
"not",
"None",
":",
"warnings",
".",
"warn",
"(",
"'rabit.int call was ignored because it has'",
"' already been initialized'",
",",
"level",
"=",
"2",
")",
"return... | Load rabit library. | [
"Load",
"rabit",
"library",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/xgboost/subtree/rabit/wrapper/rabit.py#L25-L42 | train | Load the rabit library. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/xgboost/subtree/rabit/wrapper/rabit.py | init | def init(args=None, lib='standard'):
"""Intialize the rabit module, call this once before using anything.
Parameters
----------
args: list of str, optional
The list of arguments used to initialized the rabit
usually you need to pass in sys.argv.
Defaults to sys.argv when it is N... | python | def init(args=None, lib='standard'):
"""Intialize the rabit module, call this once before using anything.
Parameters
----------
args: list of str, optional
The list of arguments used to initialized the rabit
usually you need to pass in sys.argv.
Defaults to sys.argv when it is N... | [
"def",
"init",
"(",
"args",
"=",
"None",
",",
"lib",
"=",
"'standard'",
")",
":",
"if",
"args",
"is",
"None",
":",
"args",
"=",
"sys",
".",
"argv",
"_loadlib",
"(",
"lib",
")",
"arr",
"=",
"(",
"ctypes",
".",
"c_char_p",
"*",
"len",
"(",
"args",
... | Intialize the rabit module, call this once before using anything.
Parameters
----------
args: list of str, optional
The list of arguments used to initialized the rabit
usually you need to pass in sys.argv.
Defaults to sys.argv when it is None.
lib: {'standard', 'mock', 'mpi'}
... | [
"Intialize",
"the",
"rabit",
"module",
"call",
"this",
"once",
"before",
"using",
"anything",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/xgboost/subtree/rabit/wrapper/rabit.py#L56-L73 | train | Intialize the rabit module. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/xgboost/subtree/rabit/wrapper/rabit.py | tracker_print | def tracker_print(msg):
"""Print message to the tracker.
This function can be used to communicate the information of
the progress to the tracker
Parameters
----------
msg : str
The message to be printed to tracker.
"""
if not isinstance(msg, str):
msg = str(msg)
_LI... | python | def tracker_print(msg):
"""Print message to the tracker.
This function can be used to communicate the information of
the progress to the tracker
Parameters
----------
msg : str
The message to be printed to tracker.
"""
if not isinstance(msg, str):
msg = str(msg)
_LI... | [
"def",
"tracker_print",
"(",
"msg",
")",
":",
"if",
"not",
"isinstance",
"(",
"msg",
",",
"str",
")",
":",
"msg",
"=",
"str",
"(",
"msg",
")",
"_LIB",
".",
"RabitTrackerPrint",
"(",
"ctypes",
".",
"c_char_p",
"(",
"msg",
")",
".",
"encode",
"(",
"'... | Print message to the tracker.
This function can be used to communicate the information of
the progress to the tracker
Parameters
----------
msg : str
The message to be printed to tracker. | [
"Print",
"message",
"to",
"the",
"tracker",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/xgboost/subtree/rabit/wrapper/rabit.py#L105-L118 | train | Print a message to the tracker. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/xgboost/subtree/rabit/wrapper/rabit.py | allreduce | def allreduce(data, op, prepare_fun=None):
"""Perform allreduce, return the result.
Parameters
----------
data: numpy array
Input data.
op: int
Reduction operators, can be MIN, MAX, SUM, BITOR
prepare_fun: function
Lazy preprocessing function, if it is not None, prepare_... | python | def allreduce(data, op, prepare_fun=None):
"""Perform allreduce, return the result.
Parameters
----------
data: numpy array
Input data.
op: int
Reduction operators, can be MIN, MAX, SUM, BITOR
prepare_fun: function
Lazy preprocessing function, if it is not None, prepare_... | [
"def",
"allreduce",
"(",
"data",
",",
"op",
",",
"prepare_fun",
"=",
"None",
")",
":",
"if",
"not",
"isinstance",
"(",
"data",
",",
"np",
".",
"ndarray",
")",
":",
"raise",
"Exception",
"(",
"'allreduce only takes in numpy.ndarray'",
")",
"buf",
"=",
"data... | Perform allreduce, return the result.
Parameters
----------
data: numpy array
Input data.
op: int
Reduction operators, can be MIN, MAX, SUM, BITOR
prepare_fun: function
Lazy preprocessing function, if it is not None, prepare_fun(data)
will be called by the function b... | [
"Perform",
"allreduce",
"return",
"the",
"result",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/xgboost/subtree/rabit/wrapper/rabit.py#L183-L226 | train | Perform allreduce on the array. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/xgboost/subtree/rabit/wrapper/rabit.py | load_checkpoint | def load_checkpoint(with_local=False):
"""Load latest check point.
Parameters
----------
with_local: bool, optional
whether the checkpoint contains local model
Returns
-------
tuple : tuple
if with_local: return (version, gobal_model, local_model)
else return (versi... | python | def load_checkpoint(with_local=False):
"""Load latest check point.
Parameters
----------
with_local: bool, optional
whether the checkpoint contains local model
Returns
-------
tuple : tuple
if with_local: return (version, gobal_model, local_model)
else return (versi... | [
"def",
"load_checkpoint",
"(",
"with_local",
"=",
"False",
")",
":",
"gptr",
"=",
"ctypes",
".",
"POINTER",
"(",
"ctypes",
".",
"c_char",
")",
"(",
")",
"global_len",
"=",
"ctypes",
".",
"c_ulong",
"(",
")",
"if",
"with_local",
":",
"lptr",
"=",
"ctype... | Load latest check point.
Parameters
----------
with_local: bool, optional
whether the checkpoint contains local model
Returns
-------
tuple : tuple
if with_local: return (version, gobal_model, local_model)
else return (version, gobal_model)
if returned version =... | [
"Load",
"latest",
"check",
"point",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/xgboost/subtree/rabit/wrapper/rabit.py#L242-L281 | train | Load the latest check point. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/xgboost/subtree/rabit/wrapper/rabit.py | checkpoint | def checkpoint(global_model, local_model=None):
"""Checkpoint the model.
This means we finished a stage of execution.
Every time we call check point, there is a version number which will increase by one.
Parameters
----------
global_model: anytype that can be pickled
globally shared mo... | python | def checkpoint(global_model, local_model=None):
"""Checkpoint the model.
This means we finished a stage of execution.
Every time we call check point, there is a version number which will increase by one.
Parameters
----------
global_model: anytype that can be pickled
globally shared mo... | [
"def",
"checkpoint",
"(",
"global_model",
",",
"local_model",
"=",
"None",
")",
":",
"sglobal",
"=",
"pickle",
".",
"dumps",
"(",
"global_model",
")",
"if",
"local_model",
"is",
"None",
":",
"_LIB",
".",
"RabitCheckPoint",
"(",
"sglobal",
",",
"len",
"(",
... | Checkpoint the model.
This means we finished a stage of execution.
Every time we call check point, there is a version number which will increase by one.
Parameters
----------
global_model: anytype that can be pickled
globally shared model/state when calling this function,
the calle... | [
"Checkpoint",
"the",
"model",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/xgboost/subtree/rabit/wrapper/rabit.py#L283-L314 | train | Checkpoint the model. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/object_detector/util/_output_formats.py | stack_annotations | def stack_annotations(annotations_sarray):
"""
Converts object detection annotations (ground truth or predictions) to
stacked format (an `SFrame` where each row is one object instance).
Parameters
----------
annotations_sarray: SArray
An `SArray` with unstacked predictions, exactly form... | python | def stack_annotations(annotations_sarray):
"""
Converts object detection annotations (ground truth or predictions) to
stacked format (an `SFrame` where each row is one object instance).
Parameters
----------
annotations_sarray: SArray
An `SArray` with unstacked predictions, exactly form... | [
"def",
"stack_annotations",
"(",
"annotations_sarray",
")",
":",
"_raise_error_if_not_sarray",
"(",
"annotations_sarray",
",",
"variable_name",
"=",
"'annotations_sarray'",
")",
"sf",
"=",
"_tc",
".",
"SFrame",
"(",
"{",
"'annotations'",
":",
"annotations_sarray",
"}"... | Converts object detection annotations (ground truth or predictions) to
stacked format (an `SFrame` where each row is one object instance).
Parameters
----------
annotations_sarray: SArray
An `SArray` with unstacked predictions, exactly formatted as the
annotations column when training a... | [
"Converts",
"object",
"detection",
"annotations",
"(",
"ground",
"truth",
"or",
"predictions",
")",
"to",
"stacked",
"format",
"(",
"an",
"SFrame",
"where",
"each",
"row",
"is",
"one",
"object",
"instance",
")",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/object_detector/util/_output_formats.py#L14-L63 | train | Convert an object detection annotations to a stacked SFrame. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/object_detector/util/_output_formats.py | unstack_annotations | def unstack_annotations(annotations_sframe, num_rows=None):
"""
Converts object detection annotations (ground truth or predictions) to
unstacked format (an `SArray` where each element is a list of object
instances).
Parameters
----------
annotations_sframe: SFrame
An `SFrame` with s... | python | def unstack_annotations(annotations_sframe, num_rows=None):
"""
Converts object detection annotations (ground truth or predictions) to
unstacked format (an `SArray` where each element is a list of object
instances).
Parameters
----------
annotations_sframe: SFrame
An `SFrame` with s... | [
"def",
"unstack_annotations",
"(",
"annotations_sframe",
",",
"num_rows",
"=",
"None",
")",
":",
"_raise_error_if_not_sframe",
"(",
"annotations_sframe",
",",
"variable_name",
"=",
"\"annotations_sframe\"",
")",
"cols",
"=",
"[",
"'label'",
",",
"'type'",
",",
"'coo... | Converts object detection annotations (ground truth or predictions) to
unstacked format (an `SArray` where each element is a list of object
instances).
Parameters
----------
annotations_sframe: SFrame
An `SFrame` with stacked predictions, produced by the
`stack_annotations` function... | [
"Converts",
"object",
"detection",
"annotations",
"(",
"ground",
"truth",
"or",
"predictions",
")",
"to",
"unstacked",
"format",
"(",
"an",
"SArray",
"where",
"each",
"element",
"is",
"a",
"list",
"of",
"object",
"instances",
")",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/object_detector/util/_output_formats.py#L66-L148 | train | This function converts the annotations in the original dataset to unstacked format. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/ranking_factorization_recommender.py | create | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
num_factors=32,
regularization=1e-9,
linear_regularization=1e-9,
side_data_factorization=True,
ranking_regularization=0.25,
... | python | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
num_factors=32,
regularization=1e-9,
linear_regularization=1e-9,
side_data_factorization=True,
ranking_regularization=0.25,
... | [
"def",
"create",
"(",
"observation_data",
",",
"user_id",
"=",
"'user_id'",
",",
"item_id",
"=",
"'item_id'",
",",
"target",
"=",
"None",
",",
"user_data",
"=",
"None",
",",
"item_data",
"=",
"None",
",",
"num_factors",
"=",
"32",
",",
"regularization",
"=... | Create a RankingFactorizationRecommender that learns latent factors for each
user and item and uses them to make rating predictions.
Parameters
----------
observation_data : SFrame
The dataset to use for training the model. It must contain a column of
user ids and a column of item ids. ... | [
"Create",
"a",
"RankingFactorizationRecommender",
"that",
"learns",
"latent",
"factors",
"for",
"each",
"user",
"and",
"item",
"and",
"uses",
"them",
"to",
"make",
"rating",
"predictions",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/ranking_factorization_recommender.py#L19-L270 | train | Creates a RankingFactorizationRecommender that learns latent factors for each user and item. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/mlmodel/docs/preprocess.py | preprocess | def preprocess():
"splits _sources/reference.rst into separate files"
text = open("./_sources/reference.rst", "r").read()
os.remove("./_sources/reference.rst")
if not os.path.exists("./_sources/reference"):
os.makedirs("./_sources/reference")
def pairwise(iterable):
"s -> (s0, s1)... | python | def preprocess():
"splits _sources/reference.rst into separate files"
text = open("./_sources/reference.rst", "r").read()
os.remove("./_sources/reference.rst")
if not os.path.exists("./_sources/reference"):
os.makedirs("./_sources/reference")
def pairwise(iterable):
"s -> (s0, s1)... | [
"def",
"preprocess",
"(",
")",
":",
"text",
"=",
"open",
"(",
"\"./_sources/reference.rst\"",
",",
"\"r\"",
")",
".",
"read",
"(",
")",
"os",
".",
"remove",
"(",
"\"./_sources/reference.rst\"",
")",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"\"... | splits _sources/reference.rst into separate files | [
"splits",
"_sources",
"/",
"reference",
".",
"rst",
"into",
"separate",
"files"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/mlmodel/docs/preprocess.py#L6-L29 | train | splits _sources / reference. rst into separate files | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/internal/wire_format.py | PackTag | def PackTag(field_number, wire_type):
"""Returns an unsigned 32-bit integer that encodes the field number and
wire type information in standard protocol message wire format.
Args:
field_number: Expected to be an integer in the range [1, 1 << 29)
wire_type: One of the WIRETYPE_* constants.
"""
if not ... | python | def PackTag(field_number, wire_type):
"""Returns an unsigned 32-bit integer that encodes the field number and
wire type information in standard protocol message wire format.
Args:
field_number: Expected to be an integer in the range [1, 1 << 29)
wire_type: One of the WIRETYPE_* constants.
"""
if not ... | [
"def",
"PackTag",
"(",
"field_number",
",",
"wire_type",
")",
":",
"if",
"not",
"0",
"<=",
"wire_type",
"<=",
"_WIRETYPE_MAX",
":",
"raise",
"message",
".",
"EncodeError",
"(",
"'Unknown wire type: %d'",
"%",
"wire_type",
")",
"return",
"(",
"field_number",
"<... | Returns an unsigned 32-bit integer that encodes the field number and
wire type information in standard protocol message wire format.
Args:
field_number: Expected to be an integer in the range [1, 1 << 29)
wire_type: One of the WIRETYPE_* constants. | [
"Returns",
"an",
"unsigned",
"32",
"-",
"bit",
"integer",
"that",
"encodes",
"the",
"field",
"number",
"and",
"wire",
"type",
"information",
"in",
"standard",
"protocol",
"message",
"wire",
"format",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/internal/wire_format.py#L80-L90 | train | Packs a field number and wire type into a 32 - bit integer. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/internal/wire_format.py | _VarUInt64ByteSizeNoTag | def _VarUInt64ByteSizeNoTag(uint64):
"""Returns the number of bytes required to serialize a single varint
using boundary value comparisons. (unrolled loop optimization -WPierce)
uint64 must be unsigned.
"""
if uint64 <= 0x7f: return 1
if uint64 <= 0x3fff: return 2
if uint64 <= 0x1fffff: return 3
if uint... | python | def _VarUInt64ByteSizeNoTag(uint64):
"""Returns the number of bytes required to serialize a single varint
using boundary value comparisons. (unrolled loop optimization -WPierce)
uint64 must be unsigned.
"""
if uint64 <= 0x7f: return 1
if uint64 <= 0x3fff: return 2
if uint64 <= 0x1fffff: return 3
if uint... | [
"def",
"_VarUInt64ByteSizeNoTag",
"(",
"uint64",
")",
":",
"if",
"uint64",
"<=",
"0x7f",
":",
"return",
"1",
"if",
"uint64",
"<=",
"0x3fff",
":",
"return",
"2",
"if",
"uint64",
"<=",
"0x1fffff",
":",
"return",
"3",
"if",
"uint64",
"<=",
"0xfffffff",
":",... | Returns the number of bytes required to serialize a single varint
using boundary value comparisons. (unrolled loop optimization -WPierce)
uint64 must be unsigned. | [
"Returns",
"the",
"number",
"of",
"bytes",
"required",
"to",
"serialize",
"a",
"single",
"varint",
"using",
"boundary",
"value",
"comparisons",
".",
"(",
"unrolled",
"loop",
"optimization",
"-",
"WPierce",
")",
"uint64",
"must",
"be",
"unsigned",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/internal/wire_format.py#L232-L248 | train | Returns the number of bytes required to serialize a single varint. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/style_transfer/_utils.py | _seconds_as_string | def _seconds_as_string(seconds):
"""
Returns seconds as a human-friendly string, e.g. '1d 4h 47m 41s'
"""
TIME_UNITS = [('s', 60), ('m', 60), ('h', 24), ('d', None)]
unit_strings = []
cur = max(int(seconds), 1)
for suffix, size in TIME_UNITS:
if size is not None:
cur, res... | python | def _seconds_as_string(seconds):
"""
Returns seconds as a human-friendly string, e.g. '1d 4h 47m 41s'
"""
TIME_UNITS = [('s', 60), ('m', 60), ('h', 24), ('d', None)]
unit_strings = []
cur = max(int(seconds), 1)
for suffix, size in TIME_UNITS:
if size is not None:
cur, res... | [
"def",
"_seconds_as_string",
"(",
"seconds",
")",
":",
"TIME_UNITS",
"=",
"[",
"(",
"'s'",
",",
"60",
")",
",",
"(",
"'m'",
",",
"60",
")",
",",
"(",
"'h'",
",",
"24",
")",
",",
"(",
"'d'",
",",
"None",
")",
"]",
"unit_strings",
"=",
"[",
"]",
... | Returns seconds as a human-friendly string, e.g. '1d 4h 47m 41s' | [
"Returns",
"seconds",
"as",
"a",
"human",
"-",
"friendly",
"string",
"e",
".",
"g",
".",
"1d",
"4h",
"47m",
"41s"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/style_transfer/_utils.py#L10-L24 | train | Returns a string representation of the given number of seconds. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_converter_internal.py | _get_converter_module | def _get_converter_module(sk_obj):
"""
Returns the module holding the conversion functions for a
particular model).
"""
try:
cv_idx = _converter_lookup[sk_obj.__class__]
except KeyError:
raise ValueError(
"Transformer '%s' not supported; supported transformers are... | python | def _get_converter_module(sk_obj):
"""
Returns the module holding the conversion functions for a
particular model).
"""
try:
cv_idx = _converter_lookup[sk_obj.__class__]
except KeyError:
raise ValueError(
"Transformer '%s' not supported; supported transformers are... | [
"def",
"_get_converter_module",
"(",
"sk_obj",
")",
":",
"try",
":",
"cv_idx",
"=",
"_converter_lookup",
"[",
"sk_obj",
".",
"__class__",
"]",
"except",
"KeyError",
":",
"raise",
"ValueError",
"(",
"\"Transformer '%s' not supported; supported transformers are %s.\"",
"%... | Returns the module holding the conversion functions for a
particular model). | [
"Returns",
"the",
"module",
"holding",
"the",
"conversion",
"functions",
"for",
"a",
"particular",
"model",
")",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_converter_internal.py#L87-L100 | train | Returns the module holding the conversion functions for a
particular model. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_converter_internal.py | _convert_sklearn_model | def _convert_sklearn_model(input_sk_obj, input_features = None,
output_feature_names = None, class_labels = None):
"""
Converts a generic sklearn pipeline, transformer, classifier, or regressor
into an coreML specification.
"""
if not(HAS_SKLEARN):
raise RuntimeErr... | python | def _convert_sklearn_model(input_sk_obj, input_features = None,
output_feature_names = None, class_labels = None):
"""
Converts a generic sklearn pipeline, transformer, classifier, or regressor
into an coreML specification.
"""
if not(HAS_SKLEARN):
raise RuntimeErr... | [
"def",
"_convert_sklearn_model",
"(",
"input_sk_obj",
",",
"input_features",
"=",
"None",
",",
"output_feature_names",
"=",
"None",
",",
"class_labels",
"=",
"None",
")",
":",
"if",
"not",
"(",
"HAS_SKLEARN",
")",
":",
"raise",
"RuntimeError",
"(",
"'scikit-lear... | Converts a generic sklearn pipeline, transformer, classifier, or regressor
into an coreML specification. | [
"Converts",
"a",
"generic",
"sklearn",
"pipeline",
"transformer",
"classifier",
"or",
"regressor",
"into",
"an",
"coreML",
"specification",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_converter_internal.py#L109-L324 | train | Converts a generic sklearn pipeline transformer classifier or regressor to a coreML specification. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py | TreeEnsembleBase.set_default_prediction_value | def set_default_prediction_value(self, values):
"""
Set the default prediction value(s).
The values given here form the base prediction value that the values
at activated leaves are added to. If values is a scalar, then
the output of the tree must also be 1 dimensional; otherwi... | python | def set_default_prediction_value(self, values):
"""
Set the default prediction value(s).
The values given here form the base prediction value that the values
at activated leaves are added to. If values is a scalar, then
the output of the tree must also be 1 dimensional; otherwi... | [
"def",
"set_default_prediction_value",
"(",
"self",
",",
"values",
")",
":",
"if",
"type",
"(",
"values",
")",
"is",
"not",
"list",
":",
"values",
"=",
"[",
"float",
"(",
"values",
")",
"]",
"self",
".",
"tree_parameters",
".",
"numPredictionDimensions",
"... | Set the default prediction value(s).
The values given here form the base prediction value that the values
at activated leaves are added to. If values is a scalar, then
the output of the tree must also be 1 dimensional; otherwise, values
must be a list with length matching the dimension... | [
"Set",
"the",
"default",
"prediction",
"value",
"(",
"s",
")",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py#L36-L55 | train | Sets the default prediction value for the given set of values. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py | TreeEnsembleBase.set_post_evaluation_transform | def set_post_evaluation_transform(self, value):
r"""
Set the post processing transform applied after the prediction value
from the tree ensemble.
Parameters
----------
value: str
A value denoting the transform applied. Possible values are:
- "... | python | def set_post_evaluation_transform(self, value):
r"""
Set the post processing transform applied after the prediction value
from the tree ensemble.
Parameters
----------
value: str
A value denoting the transform applied. Possible values are:
- "... | [
"def",
"set_post_evaluation_transform",
"(",
"self",
",",
"value",
")",
":",
"self",
".",
"tree_spec",
".",
"postEvaluationTransform",
"=",
"_TreeEnsemble_pb2",
".",
"TreeEnsemblePostEvaluationTransform",
".",
"Value",
"(",
"value",
")"
] | r"""
Set the post processing transform applied after the prediction value
from the tree ensemble.
Parameters
----------
value: str
A value denoting the transform applied. Possible values are:
- "NoTransform" (default). Do not apply a transform.
... | [
"r",
"Set",
"the",
"post",
"processing",
"transform",
"applied",
"after",
"the",
"prediction",
"value",
"from",
"the",
"tree",
"ensemble",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py#L57-L97 | train | r Sets the post processing transform applied after the prediction value from the tree ensemble. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py | TreeEnsembleBase.add_branch_node | def add_branch_node(self, tree_id, node_id, feature_index, feature_value,
branch_mode, true_child_id, false_child_id, relative_hit_rate = None,
missing_value_tracks_true_child = False):
"""
Add a branch node to the tree ensemble.
Parameters
----------
tre... | python | def add_branch_node(self, tree_id, node_id, feature_index, feature_value,
branch_mode, true_child_id, false_child_id, relative_hit_rate = None,
missing_value_tracks_true_child = False):
"""
Add a branch node to the tree ensemble.
Parameters
----------
tre... | [
"def",
"add_branch_node",
"(",
"self",
",",
"tree_id",
",",
"node_id",
",",
"feature_index",
",",
"feature_value",
",",
"branch_mode",
",",
"true_child_id",
",",
"false_child_id",
",",
"relative_hit_rate",
"=",
"None",
",",
"missing_value_tracks_true_child",
"=",
"F... | Add a branch node to the tree ensemble.
Parameters
----------
tree_id: int
ID of the tree to add the node to.
node_id: int
ID of the node within the tree.
feature_index: int
Index of the feature in the input being split on.
feature_... | [
"Add",
"a",
"branch",
"node",
"to",
"the",
"tree",
"ensemble",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py#L99-L186 | train | This method adds a branch node to the ensemble. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py | TreeEnsembleBase.add_leaf_node | def add_leaf_node(self, tree_id, node_id, values, relative_hit_rate = None):
"""
Add a leaf node to the tree ensemble.
Parameters
----------
tree_id: int
ID of the tree to add the node to.
node_id: int
ID of the node within the tree.
val... | python | def add_leaf_node(self, tree_id, node_id, values, relative_hit_rate = None):
"""
Add a leaf node to the tree ensemble.
Parameters
----------
tree_id: int
ID of the tree to add the node to.
node_id: int
ID of the node within the tree.
val... | [
"def",
"add_leaf_node",
"(",
"self",
",",
"tree_id",
",",
"node_id",
",",
"values",
",",
"relative_hit_rate",
"=",
"None",
")",
":",
"spec_node",
"=",
"self",
".",
"tree_parameters",
".",
"nodes",
".",
"add",
"(",
")",
"spec_node",
".",
"treeId",
"=",
"t... | Add a leaf node to the tree ensemble.
Parameters
----------
tree_id: int
ID of the tree to add the node to.
node_id: int
ID of the node within the tree.
values: [float | int | list | dict]
Value(s) at the leaf node to add to the prediction w... | [
"Add",
"a",
"leaf",
"node",
"to",
"the",
"tree",
"ensemble",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/tree_ensemble.py#L188-L235 | train | Adds a leaf node to the tree ensemble. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | create | def create (raw_properties = []):
""" Creates a new 'PropertySet' instance for the given raw properties,
or returns an already existing one.
"""
assert (is_iterable_typed(raw_properties, property.Property)
or is_iterable_typed(raw_properties, basestring))
# FIXME: propagate to caller... | python | def create (raw_properties = []):
""" Creates a new 'PropertySet' instance for the given raw properties,
or returns an already existing one.
"""
assert (is_iterable_typed(raw_properties, property.Property)
or is_iterable_typed(raw_properties, basestring))
# FIXME: propagate to caller... | [
"def",
"create",
"(",
"raw_properties",
"=",
"[",
"]",
")",
":",
"assert",
"(",
"is_iterable_typed",
"(",
"raw_properties",
",",
"property",
".",
"Property",
")",
"or",
"is_iterable_typed",
"(",
"raw_properties",
",",
"basestring",
")",
")",
"# FIXME: propagate ... | Creates a new 'PropertySet' instance for the given raw properties,
or returns an already existing one. | [
"Creates",
"a",
"new",
"PropertySet",
"instance",
"for",
"the",
"given",
"raw",
"properties",
"or",
"returns",
"an",
"already",
"existing",
"one",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L36-L61 | train | Creates a new PropertySet instance for the given raw properties and returns an existing one. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | create_with_validation | def create_with_validation (raw_properties):
""" Creates new 'PropertySet' instances after checking
that all properties are valid and converting implicit
properties into gristed form.
"""
assert is_iterable_typed(raw_properties, basestring)
properties = [property.create_from_string(s) fo... | python | def create_with_validation (raw_properties):
""" Creates new 'PropertySet' instances after checking
that all properties are valid and converting implicit
properties into gristed form.
"""
assert is_iterable_typed(raw_properties, basestring)
properties = [property.create_from_string(s) fo... | [
"def",
"create_with_validation",
"(",
"raw_properties",
")",
":",
"assert",
"is_iterable_typed",
"(",
"raw_properties",
",",
"basestring",
")",
"properties",
"=",
"[",
"property",
".",
"create_from_string",
"(",
"s",
")",
"for",
"s",
"in",
"raw_properties",
"]",
... | Creates new 'PropertySet' instances after checking
that all properties are valid and converting implicit
properties into gristed form. | [
"Creates",
"new",
"PropertySet",
"instances",
"after",
"checking",
"that",
"all",
"properties",
"are",
"valid",
"and",
"converting",
"implicit",
"properties",
"into",
"gristed",
"form",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L63-L72 | train | Creates a new PropertySet instance after checking that all properties are valid and converting implicit
properties into gristed form. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | create_from_user_input | def create_from_user_input(raw_properties, jamfile_module, location):
"""Creates a property-set from the input given by the user, in the
context of 'jamfile-module' at 'location'"""
assert is_iterable_typed(raw_properties, basestring)
assert isinstance(jamfile_module, basestring)
assert isinstance(l... | python | def create_from_user_input(raw_properties, jamfile_module, location):
"""Creates a property-set from the input given by the user, in the
context of 'jamfile-module' at 'location'"""
assert is_iterable_typed(raw_properties, basestring)
assert isinstance(jamfile_module, basestring)
assert isinstance(l... | [
"def",
"create_from_user_input",
"(",
"raw_properties",
",",
"jamfile_module",
",",
"location",
")",
":",
"assert",
"is_iterable_typed",
"(",
"raw_properties",
",",
"basestring",
")",
"assert",
"isinstance",
"(",
"jamfile_module",
",",
"basestring",
")",
"assert",
"... | Creates a property-set from the input given by the user, in the
context of 'jamfile-module' at 'location | [
"Creates",
"a",
"property",
"-",
"set",
"from",
"the",
"input",
"given",
"by",
"the",
"user",
"in",
"the",
"context",
"of",
"jamfile",
"-",
"module",
"at",
"location"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L79-L94 | train | Creates a property - set from the input given by the user. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | refine_from_user_input | def refine_from_user_input(parent_requirements, specification, jamfile_module,
location):
"""Refines requirements with requirements provided by the user.
Specially handles "-<property>value" syntax in specification
to remove given requirements.
- parent-requirements -- prope... | python | def refine_from_user_input(parent_requirements, specification, jamfile_module,
location):
"""Refines requirements with requirements provided by the user.
Specially handles "-<property>value" syntax in specification
to remove given requirements.
- parent-requirements -- prope... | [
"def",
"refine_from_user_input",
"(",
"parent_requirements",
",",
"specification",
",",
"jamfile_module",
",",
"location",
")",
":",
"assert",
"isinstance",
"(",
"parent_requirements",
",",
"PropertySet",
")",
"assert",
"is_iterable_typed",
"(",
"specification",
",",
... | Refines requirements with requirements provided by the user.
Specially handles "-<property>value" syntax in specification
to remove given requirements.
- parent-requirements -- property-set object with requirements
to refine
- specification -- string list of requirements provided by the use
... | [
"Refines",
"requirements",
"with",
"requirements",
"provided",
"by",
"the",
"user",
".",
"Specially",
"handles",
"-",
"<property",
">",
"value",
"syntax",
"in",
"specification",
"to",
"remove",
"given",
"requirements",
".",
"-",
"parent",
"-",
"requirements",
"-... | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L97-L140 | train | Refines requirements with requirements provided by the user. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.base | def base (self):
""" Returns properties that are neither incidental nor free.
"""
result = [p for p in self.lazy_properties
if not(p.feature.incidental or p.feature.free)]
result.extend(self.base_)
return result | python | def base (self):
""" Returns properties that are neither incidental nor free.
"""
result = [p for p in self.lazy_properties
if not(p.feature.incidental or p.feature.free)]
result.extend(self.base_)
return result | [
"def",
"base",
"(",
"self",
")",
":",
"result",
"=",
"[",
"p",
"for",
"p",
"in",
"self",
".",
"lazy_properties",
"if",
"not",
"(",
"p",
".",
"feature",
".",
"incidental",
"or",
"p",
".",
"feature",
".",
"free",
")",
"]",
"result",
".",
"extend",
... | Returns properties that are neither incidental nor free. | [
"Returns",
"properties",
"that",
"are",
"neither",
"incidental",
"nor",
"free",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L264-L270 | train | Returns a list of properties that are neither incidental nor free. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.free | def free (self):
""" Returns free properties which are not dependency properties.
"""
result = [p for p in self.lazy_properties
if not p.feature.incidental and p.feature.free]
result.extend(self.free_)
return result | python | def free (self):
""" Returns free properties which are not dependency properties.
"""
result = [p for p in self.lazy_properties
if not p.feature.incidental and p.feature.free]
result.extend(self.free_)
return result | [
"def",
"free",
"(",
"self",
")",
":",
"result",
"=",
"[",
"p",
"for",
"p",
"in",
"self",
".",
"lazy_properties",
"if",
"not",
"p",
".",
"feature",
".",
"incidental",
"and",
"p",
".",
"feature",
".",
"free",
"]",
"result",
".",
"extend",
"(",
"self"... | Returns free properties which are not dependency properties. | [
"Returns",
"free",
"properties",
"which",
"are",
"not",
"dependency",
"properties",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L272-L278 | train | Returns the set of free properties which are not dependency properties. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.dependency | def dependency (self):
""" Returns dependency properties.
"""
result = [p for p in self.lazy_properties if p.feature.dependency]
result.extend(self.dependency_)
return self.dependency_ | python | def dependency (self):
""" Returns dependency properties.
"""
result = [p for p in self.lazy_properties if p.feature.dependency]
result.extend(self.dependency_)
return self.dependency_ | [
"def",
"dependency",
"(",
"self",
")",
":",
"result",
"=",
"[",
"p",
"for",
"p",
"in",
"self",
".",
"lazy_properties",
"if",
"p",
".",
"feature",
".",
"dependency",
"]",
"result",
".",
"extend",
"(",
"self",
".",
"dependency_",
")",
"return",
"self",
... | Returns dependency properties. | [
"Returns",
"dependency",
"properties",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L283-L288 | train | Returns the dependency properties. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.non_dependency | def non_dependency (self):
""" Returns properties that are not dependencies.
"""
result = [p for p in self.lazy_properties if not p.feature.dependency]
result.extend(self.non_dependency_)
return result | python | def non_dependency (self):
""" Returns properties that are not dependencies.
"""
result = [p for p in self.lazy_properties if not p.feature.dependency]
result.extend(self.non_dependency_)
return result | [
"def",
"non_dependency",
"(",
"self",
")",
":",
"result",
"=",
"[",
"p",
"for",
"p",
"in",
"self",
".",
"lazy_properties",
"if",
"not",
"p",
".",
"feature",
".",
"dependency",
"]",
"result",
".",
"extend",
"(",
"self",
".",
"non_dependency_",
")",
"ret... | Returns properties that are not dependencies. | [
"Returns",
"properties",
"that",
"are",
"not",
"dependencies",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L290-L295 | train | Returns properties that are not dependencies. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.incidental | def incidental (self):
""" Returns incidental properties.
"""
result = [p for p in self.lazy_properties if p.feature.incidental]
result.extend(self.incidental_)
return result | python | def incidental (self):
""" Returns incidental properties.
"""
result = [p for p in self.lazy_properties if p.feature.incidental]
result.extend(self.incidental_)
return result | [
"def",
"incidental",
"(",
"self",
")",
":",
"result",
"=",
"[",
"p",
"for",
"p",
"in",
"self",
".",
"lazy_properties",
"if",
"p",
".",
"feature",
".",
"incidental",
"]",
"result",
".",
"extend",
"(",
"self",
".",
"incidental_",
")",
"return",
"result"
... | Returns incidental properties. | [
"Returns",
"incidental",
"properties",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L307-L312 | train | Returns the list of incidental properties. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.refine | def refine (self, requirements):
""" Refines this set's properties using the requirements passed as an argument.
"""
assert isinstance(requirements, PropertySet)
if requirements not in self.refined_:
r = property.refine(self.all_, requirements.all_)
self.refined_... | python | def refine (self, requirements):
""" Refines this set's properties using the requirements passed as an argument.
"""
assert isinstance(requirements, PropertySet)
if requirements not in self.refined_:
r = property.refine(self.all_, requirements.all_)
self.refined_... | [
"def",
"refine",
"(",
"self",
",",
"requirements",
")",
":",
"assert",
"isinstance",
"(",
"requirements",
",",
"PropertySet",
")",
"if",
"requirements",
"not",
"in",
"self",
".",
"refined_",
":",
"r",
"=",
"property",
".",
"refine",
"(",
"self",
".",
"al... | Refines this set's properties using the requirements passed as an argument. | [
"Refines",
"this",
"set",
"s",
"properties",
"using",
"the",
"requirements",
"passed",
"as",
"an",
"argument",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L314-L323 | train | Refines this set s properties using the requirements passed as an argument. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.target_path | def target_path (self):
""" Computes the target path that should be used for
target with these properties.
Returns a tuple of
- the computed path
- if the path is relative to build directory, a value of
'true'.
"""
if not self.t... | python | def target_path (self):
""" Computes the target path that should be used for
target with these properties.
Returns a tuple of
- the computed path
- if the path is relative to build directory, a value of
'true'.
"""
if not self.t... | [
"def",
"target_path",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"target_path_",
":",
"# The <location> feature can be used to explicitly",
"# change the location of generated targets",
"l",
"=",
"self",
".",
"get",
"(",
"'<location>'",
")",
"if",
"l",
":",
"c... | Computes the target path that should be used for
target with these properties.
Returns a tuple of
- the computed path
- if the path is relative to build directory, a value of
'true'. | [
"Computes",
"the",
"target",
"path",
"that",
"should",
"be",
"used",
"for",
"target",
"with",
"these",
"properties",
".",
"Returns",
"a",
"tuple",
"of",
"-",
"the",
"computed",
"path",
"-",
"if",
"the",
"path",
"is",
"relative",
"to",
"build",
"directory",... | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L395-L439 | train | Computes the target path that should be used for the target with these properties. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.add | def add (self, ps):
""" Creates a new property set containing the properties in this one,
plus the ones of the property set passed as argument.
"""
assert isinstance(ps, PropertySet)
if ps not in self.added_:
self.added_[ps] = create(self.all_ + ps.all())
... | python | def add (self, ps):
""" Creates a new property set containing the properties in this one,
plus the ones of the property set passed as argument.
"""
assert isinstance(ps, PropertySet)
if ps not in self.added_:
self.added_[ps] = create(self.all_ + ps.all())
... | [
"def",
"add",
"(",
"self",
",",
"ps",
")",
":",
"assert",
"isinstance",
"(",
"ps",
",",
"PropertySet",
")",
"if",
"ps",
"not",
"in",
"self",
".",
"added_",
":",
"self",
".",
"added_",
"[",
"ps",
"]",
"=",
"create",
"(",
"self",
".",
"all_",
"+",
... | Creates a new property set containing the properties in this one,
plus the ones of the property set passed as argument. | [
"Creates",
"a",
"new",
"property",
"set",
"containing",
"the",
"properties",
"in",
"this",
"one",
"plus",
"the",
"ones",
"of",
"the",
"property",
"set",
"passed",
"as",
"argument",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L441-L448 | train | Adds the properties in this one plus the ones of the passed property set. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.get | def get (self, feature):
""" Returns all values of 'feature'.
"""
if type(feature) == type([]):
feature = feature[0]
if not isinstance(feature, b2.build.feature.Feature):
feature = b2.build.feature.get(feature)
assert isinstance(feature, b2.build.feature.F... | python | def get (self, feature):
""" Returns all values of 'feature'.
"""
if type(feature) == type([]):
feature = feature[0]
if not isinstance(feature, b2.build.feature.Feature):
feature = b2.build.feature.get(feature)
assert isinstance(feature, b2.build.feature.F... | [
"def",
"get",
"(",
"self",
",",
"feature",
")",
":",
"if",
"type",
"(",
"feature",
")",
"==",
"type",
"(",
"[",
"]",
")",
":",
"feature",
"=",
"feature",
"[",
"0",
"]",
"if",
"not",
"isinstance",
"(",
"feature",
",",
"b2",
".",
"build",
".",
"f... | Returns all values of 'feature'. | [
"Returns",
"all",
"values",
"of",
"feature",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L457-L474 | train | Returns all values of feature. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/property_set.py | PropertySet.get_properties | def get_properties(self, feature):
"""Returns all contained properties associated with 'feature'"""
if not isinstance(feature, b2.build.feature.Feature):
feature = b2.build.feature.get(feature)
assert isinstance(feature, b2.build.feature.Feature)
result = []
for p in... | python | def get_properties(self, feature):
"""Returns all contained properties associated with 'feature'"""
if not isinstance(feature, b2.build.feature.Feature):
feature = b2.build.feature.get(feature)
assert isinstance(feature, b2.build.feature.Feature)
result = []
for p in... | [
"def",
"get_properties",
"(",
"self",
",",
"feature",
")",
":",
"if",
"not",
"isinstance",
"(",
"feature",
",",
"b2",
".",
"build",
".",
"feature",
".",
"Feature",
")",
":",
"feature",
"=",
"b2",
".",
"build",
".",
"feature",
".",
"get",
"(",
"featur... | Returns all contained properties associated with 'feature | [
"Returns",
"all",
"contained",
"properties",
"associated",
"with",
"feature"
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/tools/build/src/build/property_set.py#L477-L487 | train | Returns all contained properties associated with feature | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _create | def _create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
ranking=True,
verbose=True):
"""
A unified interface for training recommender models. Based on simple
characteristics of the data, a type of model is s... | python | def _create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
ranking=True,
verbose=True):
"""
A unified interface for training recommender models. Based on simple
characteristics of the data, a type of model is s... | [
"def",
"_create",
"(",
"observation_data",
",",
"user_id",
"=",
"'user_id'",
",",
"item_id",
"=",
"'item_id'",
",",
"target",
"=",
"None",
",",
"user_data",
"=",
"None",
",",
"item_data",
"=",
"None",
",",
"ranking",
"=",
"True",
",",
"verbose",
"=",
"Tr... | A unified interface for training recommender models. Based on simple
characteristics of the data, a type of model is selected and trained. The
trained model can be used to predict ratings and make recommendations.
To use specific options of a desired model, use the ``create`` function
of the correspond... | [
"A",
"unified",
"interface",
"for",
"training",
"recommender",
"models",
".",
"Based",
"on",
"simple",
"characteristics",
"of",
"the",
"data",
"a",
"type",
"of",
"model",
"is",
"selected",
"and",
"trained",
".",
"The",
"trained",
"model",
"can",
"be",
"used"... | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L24-L175 | train | Create a new unkown version of the training recommender model. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | compare_models | def compare_models(dataset, models, model_names=None, user_sample=1.0,
metric='auto',
target=None,
exclude_known_for_precision_recall=True,
make_plot=False,
verbose=True,
**kwargs):
"""
Compare the ... | python | def compare_models(dataset, models, model_names=None, user_sample=1.0,
metric='auto',
target=None,
exclude_known_for_precision_recall=True,
make_plot=False,
verbose=True,
**kwargs):
"""
Compare the ... | [
"def",
"compare_models",
"(",
"dataset",
",",
"models",
",",
"model_names",
"=",
"None",
",",
"user_sample",
"=",
"1.0",
",",
"metric",
"=",
"'auto'",
",",
"target",
"=",
"None",
",",
"exclude_known_for_precision_recall",
"=",
"True",
",",
"make_plot",
"=",
... | Compare the prediction or recommendation performance of recommender models
on a common test dataset.
Models that are trained to predict ratings are compared separately from
models that are trained without target ratings. The ratings prediction
models are compared on root-mean-squared error, and the re... | [
"Compare",
"the",
"prediction",
"or",
"recommendation",
"performance",
"of",
"recommender",
"models",
"on",
"a",
"common",
"test",
"dataset",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L177-L328 | train | Compare the model models with the training data. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | precision_recall_by_user | def precision_recall_by_user(observed_user_items,
recommendations,
cutoffs=[10]):
"""
Compute precision and recall at a given cutoff for each user. In information
retrieval terms, precision represents the ratio of relevant, retrieved items
to the... | python | def precision_recall_by_user(observed_user_items,
recommendations,
cutoffs=[10]):
"""
Compute precision and recall at a given cutoff for each user. In information
retrieval terms, precision represents the ratio of relevant, retrieved items
to the... | [
"def",
"precision_recall_by_user",
"(",
"observed_user_items",
",",
"recommendations",
",",
"cutoffs",
"=",
"[",
"10",
"]",
")",
":",
"assert",
"type",
"(",
"observed_user_items",
")",
"==",
"_SFrame",
"assert",
"type",
"(",
"recommendations",
")",
"==",
"_SFram... | Compute precision and recall at a given cutoff for each user. In information
retrieval terms, precision represents the ratio of relevant, retrieved items
to the number of relevant items. Recall represents the ratio of relevant,
retrieved items to the number of relevant items.
Let :math:`p_k` be a vecto... | [
"Compute",
"precision",
"and",
"recall",
"at",
"a",
"given",
"cutoff",
"for",
"each",
"user",
".",
"In",
"information",
"retrieval",
"terms",
"precision",
"represents",
"the",
"ratio",
"of",
"relevant",
"retrieved",
"items",
"to",
"the",
"number",
"of",
"relev... | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L331-L427 | train | Compute precision and recall for each user in the information tree. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | random_split_by_user | def random_split_by_user(dataset,
user_id='user_id',
item_id='item_id',
max_num_users=1000,
item_test_proportion=.2,
random_seed=0):
"""Create a recommender-friendly train-test split of the p... | python | def random_split_by_user(dataset,
user_id='user_id',
item_id='item_id',
max_num_users=1000,
item_test_proportion=.2,
random_seed=0):
"""Create a recommender-friendly train-test split of the p... | [
"def",
"random_split_by_user",
"(",
"dataset",
",",
"user_id",
"=",
"'user_id'",
",",
"item_id",
"=",
"'item_id'",
",",
"max_num_users",
"=",
"1000",
",",
"item_test_proportion",
"=",
".2",
",",
"random_seed",
"=",
"0",
")",
":",
"assert",
"user_id",
"in",
"... | Create a recommender-friendly train-test split of the provided data set.
The test dataset is generated by first choosing `max_num_users` out of the
total number of users in `dataset`. Then, for each of the chosen test users,
a portion of the user's items (determined by `item_test_proportion`) is
random... | [
"Create",
"a",
"recommender",
"-",
"friendly",
"train",
"-",
"test",
"split",
"of",
"the",
"provided",
"data",
"set",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L430-L508 | train | Generates a train - test split of the provided dataset. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender._list_fields | def _list_fields(self):
"""
Get the current settings of the model. The keys depend on the type of
model.
Returns
-------
out : list
A list of fields that can be queried using the ``get`` method.
"""
response = self.__proxy__.list_fields()
... | python | def _list_fields(self):
"""
Get the current settings of the model. The keys depend on the type of
model.
Returns
-------
out : list
A list of fields that can be queried using the ``get`` method.
"""
response = self.__proxy__.list_fields()
... | [
"def",
"_list_fields",
"(",
"self",
")",
":",
"response",
"=",
"self",
".",
"__proxy__",
".",
"list_fields",
"(",
")",
"return",
"[",
"s",
"for",
"s",
"in",
"response",
"[",
"'value'",
"]",
"if",
"not",
"s",
".",
"startswith",
"(",
"\"_\"",
")",
"]"
... | Get the current settings of the model. The keys depend on the type of
model.
Returns
-------
out : list
A list of fields that can be queried using the ``get`` method. | [
"Get",
"the",
"current",
"settings",
"of",
"the",
"model",
".",
"The",
"keys",
"depend",
"on",
"the",
"type",
"of",
"model",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L543-L555 | train | Returns a list of fields that can be queried using the get method. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender._get_summary_struct | def _get_summary_struct(self):
"""
Returns a structured description of the model, including (where relevant)
the schema of the training data, description of the training data,
training statistics, and model hyperparameters.
Returns
-------
sections : list (of lis... | python | def _get_summary_struct(self):
"""
Returns a structured description of the model, including (where relevant)
the schema of the training data, description of the training data,
training statistics, and model hyperparameters.
Returns
-------
sections : list (of lis... | [
"def",
"_get_summary_struct",
"(",
"self",
")",
":",
"stats",
"=",
"self",
".",
"_list_fields",
"(",
")",
"options",
"=",
"self",
".",
"_get_current_options",
"(",
")",
"section_titles",
"=",
"[",
"]",
"sections",
"=",
"[",
"]",
"observation_columns",
"=",
... | Returns a structured description of the model, including (where relevant)
the schema of the training data, description of the training data,
training statistics, and model hyperparameters.
Returns
-------
sections : list (of list of tuples)
A list of summary sections... | [
"Returns",
"a",
"structured",
"description",
"of",
"the",
"model",
"including",
"(",
"where",
"relevant",
")",
"the",
"schema",
"of",
"the",
"training",
"data",
"description",
"of",
"the",
"training",
"data",
"training",
"statistics",
"and",
"model",
"hyperparam... | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L634-L782 | train | Returns a structured description of the model. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender._set_current_options | def _set_current_options(self, options):
"""
Set current options for a model.
Parameters
----------
options : dict
A dictionary of the desired option settings. The key should be the name
of the option and each value is the desired value of the option.
... | python | def _set_current_options(self, options):
"""
Set current options for a model.
Parameters
----------
options : dict
A dictionary of the desired option settings. The key should be the name
of the option and each value is the desired value of the option.
... | [
"def",
"_set_current_options",
"(",
"self",
",",
"options",
")",
":",
"opts",
"=",
"self",
".",
"_get_current_options",
"(",
")",
"opts",
".",
"update",
"(",
"options",
")",
"response",
"=",
"self",
".",
"__proxy__",
".",
"set_current_options",
"(",
"opts",
... | Set current options for a model.
Parameters
----------
options : dict
A dictionary of the desired option settings. The key should be the name
of the option and each value is the desired value of the option. | [
"Set",
"current",
"options",
"for",
"a",
"model",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L804-L818 | train | Set the current options for a model. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.__prepare_dataset_parameter | def __prepare_dataset_parameter(self, dataset):
"""
Processes the dataset parameter for type correctness.
Returns it as an SFrame.
"""
# Translate the dataset argument into the proper type
if not isinstance(dataset, _SFrame):
def raise_dataset_type_exception(... | python | def __prepare_dataset_parameter(self, dataset):
"""
Processes the dataset parameter for type correctness.
Returns it as an SFrame.
"""
# Translate the dataset argument into the proper type
if not isinstance(dataset, _SFrame):
def raise_dataset_type_exception(... | [
"def",
"__prepare_dataset_parameter",
"(",
"self",
",",
"dataset",
")",
":",
"# Translate the dataset argument into the proper type",
"if",
"not",
"isinstance",
"(",
"dataset",
",",
"_SFrame",
")",
":",
"def",
"raise_dataset_type_exception",
"(",
")",
":",
"raise",
"T... | Processes the dataset parameter for type correctness.
Returns it as an SFrame. | [
"Processes",
"the",
"dataset",
"parameter",
"for",
"type",
"correctness",
".",
"Returns",
"it",
"as",
"an",
"SFrame",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L820-L843 | train | Processes the dataset parameter for type correctness. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender._get_data_schema | def _get_data_schema(self):
"""
Returns a dictionary of (column : type) for the data used in the
model.
"""
if not hasattr(self, "_data_schema"):
response = self.__proxy__.get_data_schema()
self._data_schema = {k : _turicreate._cython.cy_flexible_type.py... | python | def _get_data_schema(self):
"""
Returns a dictionary of (column : type) for the data used in the
model.
"""
if not hasattr(self, "_data_schema"):
response = self.__proxy__.get_data_schema()
self._data_schema = {k : _turicreate._cython.cy_flexible_type.py... | [
"def",
"_get_data_schema",
"(",
"self",
")",
":",
"if",
"not",
"hasattr",
"(",
"self",
",",
"\"_data_schema\"",
")",
":",
"response",
"=",
"self",
".",
"__proxy__",
".",
"get_data_schema",
"(",
")",
"self",
".",
"_data_schema",
"=",
"{",
"k",
":",
"_turi... | Returns a dictionary of (column : type) for the data used in the
model. | [
"Returns",
"a",
"dictionary",
"of",
"(",
"column",
":",
"type",
")",
"for",
"the",
"data",
"used",
"in",
"the",
"model",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L845-L857 | train | Returns a dictionary of column type for the data used in the
model. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.predict | def predict(self, dataset,
new_observation_data=None, new_user_data=None, new_item_data=None):
"""
Return a score prediction for the user ids and item ids in the provided
data set.
Parameters
----------
dataset : SFrame
Dataset in the same for... | python | def predict(self, dataset,
new_observation_data=None, new_user_data=None, new_item_data=None):
"""
Return a score prediction for the user ids and item ids in the provided
data set.
Parameters
----------
dataset : SFrame
Dataset in the same for... | [
"def",
"predict",
"(",
"self",
",",
"dataset",
",",
"new_observation_data",
"=",
"None",
",",
"new_user_data",
"=",
"None",
",",
"new_item_data",
"=",
"None",
")",
":",
"if",
"new_observation_data",
"is",
"None",
":",
"new_observation_data",
"=",
"_SFrame",
"(... | Return a score prediction for the user ids and item ids in the provided
data set.
Parameters
----------
dataset : SFrame
Dataset in the same form used for training.
new_observation_data : SFrame, optional
``new_observation_data`` gives additional observa... | [
"Return",
"a",
"score",
"prediction",
"for",
"the",
"user",
"ids",
"and",
"item",
"ids",
"in",
"the",
"provided",
"data",
"set",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L859-L925 | train | Predict the user and item ids of the provided data set. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.get_similar_items | def get_similar_items(self, items=None, k=10, verbose=False):
"""
Get the k most similar items for each item in items.
Each type of recommender has its own model for the similarity
between items. For example, the item_similarity_recommender will
return the most similar items acc... | python | def get_similar_items(self, items=None, k=10, verbose=False):
"""
Get the k most similar items for each item in items.
Each type of recommender has its own model for the similarity
between items. For example, the item_similarity_recommender will
return the most similar items acc... | [
"def",
"get_similar_items",
"(",
"self",
",",
"items",
"=",
"None",
",",
"k",
"=",
"10",
",",
"verbose",
"=",
"False",
")",
":",
"if",
"items",
"is",
"None",
":",
"get_all_items",
"=",
"True",
"items",
"=",
"_SArray",
"(",
")",
"else",
":",
"get_all_... | Get the k most similar items for each item in items.
Each type of recommender has its own model for the similarity
between items. For example, the item_similarity_recommender will
return the most similar items according to the user-chosen
similarity; the factorization_recommender will r... | [
"Get",
"the",
"k",
"most",
"similar",
"items",
"for",
"each",
"item",
"in",
"items",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L927-L988 | train | Returns the k most similar items for each item in items. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.get_similar_users | def get_similar_users(self, users=None, k=10):
"""Get the k most similar users for each entry in `users`.
Each type of recommender has its own model for the similarity
between users. For example, the factorization_recommender will
return the nearest users based on the cosine similarity
... | python | def get_similar_users(self, users=None, k=10):
"""Get the k most similar users for each entry in `users`.
Each type of recommender has its own model for the similarity
between users. For example, the factorization_recommender will
return the nearest users based on the cosine similarity
... | [
"def",
"get_similar_users",
"(",
"self",
",",
"users",
"=",
"None",
",",
"k",
"=",
"10",
")",
":",
"if",
"users",
"is",
"None",
":",
"get_all_users",
"=",
"True",
"users",
"=",
"_SArray",
"(",
")",
"else",
":",
"get_all_users",
"=",
"False",
"if",
"i... | Get the k most similar users for each entry in `users`.
Each type of recommender has its own model for the similarity
between users. For example, the factorization_recommender will
return the nearest users based on the cosine similarity
between latent user factors. (This method is not ... | [
"Get",
"the",
"k",
"most",
"similar",
"users",
"for",
"each",
"entry",
"in",
"users",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L990-L1053 | train | Return the k most similar users for each user in users. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.recommend | def recommend(self, users=None, k=10, exclude=None, items=None,
new_observation_data=None, new_user_data=None, new_item_data=None,
exclude_known=True, diversity=0, random_seed=None,
verbose=True):
"""
Recommend the ``k`` highest scored items for each... | python | def recommend(self, users=None, k=10, exclude=None, items=None,
new_observation_data=None, new_user_data=None, new_item_data=None,
exclude_known=True, diversity=0, random_seed=None,
verbose=True):
"""
Recommend the ``k`` highest scored items for each... | [
"def",
"recommend",
"(",
"self",
",",
"users",
"=",
"None",
",",
"k",
"=",
"10",
",",
"exclude",
"=",
"None",
",",
"items",
"=",
"None",
",",
"new_observation_data",
"=",
"None",
",",
"new_user_data",
"=",
"None",
",",
"new_item_data",
"=",
"None",
","... | Recommend the ``k`` highest scored items for each user.
Parameters
----------
users : SArray, SFrame, or list, optional
Users or observation queries for which to make recommendations.
For list, SArray, and single-column inputs, this is simply a set
of user I... | [
"Recommend",
"the",
"k",
"highest",
"scored",
"items",
"for",
"each",
"user",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1056-L1308 | train | This method recommends the highest scored items for each user in the set of items. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.recommend_from_interactions | def recommend_from_interactions(
self, observed_items, k=10, exclude=None, items=None,
new_user_data=None, new_item_data=None,
exclude_known=True, diversity=0, random_seed=None,
verbose=True):
"""
Recommend the ``k`` highest scored items based on the
... | python | def recommend_from_interactions(
self, observed_items, k=10, exclude=None, items=None,
new_user_data=None, new_item_data=None,
exclude_known=True, diversity=0, random_seed=None,
verbose=True):
"""
Recommend the ``k`` highest scored items based on the
... | [
"def",
"recommend_from_interactions",
"(",
"self",
",",
"observed_items",
",",
"k",
"=",
"10",
",",
"exclude",
"=",
"None",
",",
"items",
"=",
"None",
",",
"new_user_data",
"=",
"None",
",",
"new_item_data",
"=",
"None",
",",
"exclude_known",
"=",
"True",
... | Recommend the ``k`` highest scored items based on the
interactions given in `observed_items.`
Parameters
----------
observed_items : SArray, SFrame, or list
A list/SArray of items to use to make recommendations, or
an SFrame of items and optionally ratings and/or... | [
"Recommend",
"the",
"k",
"highest",
"scored",
"items",
"based",
"on",
"the",
"interactions",
"given",
"in",
"observed_items",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1310-L1470 | train | This function recommends the most scored items based on the given interactions. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.evaluate_precision_recall | def evaluate_precision_recall(self, dataset, cutoffs=list(range(1,11,1))+list(range(11,50,5)),
skip_set=None, exclude_known=True,
verbose=True, **kwargs):
"""
Compute a model's precision and recall scores for a particular dataset.
... | python | def evaluate_precision_recall(self, dataset, cutoffs=list(range(1,11,1))+list(range(11,50,5)),
skip_set=None, exclude_known=True,
verbose=True, **kwargs):
"""
Compute a model's precision and recall scores for a particular dataset.
... | [
"def",
"evaluate_precision_recall",
"(",
"self",
",",
"dataset",
",",
"cutoffs",
"=",
"list",
"(",
"range",
"(",
"1",
",",
"11",
",",
"1",
")",
")",
"+",
"list",
"(",
"range",
"(",
"11",
",",
"50",
",",
"5",
")",
")",
",",
"skip_set",
"=",
"None"... | Compute a model's precision and recall scores for a particular dataset.
Parameters
----------
dataset : SFrame
An SFrame in the same format as the one used during training.
This will be compared to the model's recommendations, which exclude
the (user, item) p... | [
"Compute",
"a",
"model",
"s",
"precision",
"and",
"recall",
"scores",
"for",
"a",
"particular",
"dataset",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1492-L1574 | train | Compute a model s precision and recall scores for a particular dataset. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.evaluate_rmse | def evaluate_rmse(self, dataset, target):
"""
Evaluate the prediction error for each user-item pair in the given data
set.
Parameters
----------
dataset : SFrame
An SFrame in the same format as the one used during training.
target : str
T... | python | def evaluate_rmse(self, dataset, target):
"""
Evaluate the prediction error for each user-item pair in the given data
set.
Parameters
----------
dataset : SFrame
An SFrame in the same format as the one used during training.
target : str
T... | [
"def",
"evaluate_rmse",
"(",
"self",
",",
"dataset",
",",
"target",
")",
":",
"assert",
"target",
"in",
"dataset",
".",
"column_names",
"(",
")",
",",
"'Provided dataset must contain a target column with the same \\\n name as the target used during training.'",
... | Evaluate the prediction error for each user-item pair in the given data
set.
Parameters
----------
dataset : SFrame
An SFrame in the same format as the one used during training.
target : str
The name of the target rating column in `dataset`.
Ret... | [
"Evaluate",
"the",
"prediction",
"error",
"for",
"each",
"user",
"-",
"item",
"pair",
"in",
"the",
"given",
"data",
"set",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1576-L1635 | train | Evaluate the prediction error for each user - item pair in the given data set and target. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.evaluate | def evaluate(self, dataset, metric='auto',
exclude_known_for_precision_recall=True,
target=None,
verbose=True, **kwargs):
r"""
Evaluate the model's ability to make rating predictions or
recommendations.
If the model is trained to predic... | python | def evaluate(self, dataset, metric='auto',
exclude_known_for_precision_recall=True,
target=None,
verbose=True, **kwargs):
r"""
Evaluate the model's ability to make rating predictions or
recommendations.
If the model is trained to predic... | [
"def",
"evaluate",
"(",
"self",
",",
"dataset",
",",
"metric",
"=",
"'auto'",
",",
"exclude_known_for_precision_recall",
"=",
"True",
",",
"target",
"=",
"None",
",",
"verbose",
"=",
"True",
",",
"*",
"*",
"kwargs",
")",
":",
"ret",
"=",
"{",
"}",
"dat... | r"""
Evaluate the model's ability to make rating predictions or
recommendations.
If the model is trained to predict a particular target, the
default metric used for model comparison is root-mean-squared error
(RMSE). Suppose :math:`y` and :math:`\widehat{y}` are vectors of lengt... | [
"r",
"Evaluate",
"the",
"model",
"s",
"ability",
"to",
"make",
"rating",
"predictions",
"or",
"recommendations",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1637-L1761 | train | r Evaluates the model s ability to make rating predictions or recommendations or model comparison. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender._get_popularity_baseline | def _get_popularity_baseline(self):
"""
Returns a new popularity model matching the data set this model was
trained with. Can be used for comparison purposes.
"""
response = self.__proxy__.get_popularity_baseline()
from .popularity_recommender import PopularityRecommen... | python | def _get_popularity_baseline(self):
"""
Returns a new popularity model matching the data set this model was
trained with. Can be used for comparison purposes.
"""
response = self.__proxy__.get_popularity_baseline()
from .popularity_recommender import PopularityRecommen... | [
"def",
"_get_popularity_baseline",
"(",
"self",
")",
":",
"response",
"=",
"self",
".",
"__proxy__",
".",
"get_popularity_baseline",
"(",
")",
"from",
".",
"popularity_recommender",
"import",
"PopularityRecommender",
"return",
"PopularityRecommender",
"(",
"response",
... | Returns a new popularity model matching the data set this model was
trained with. Can be used for comparison purposes. | [
"Returns",
"a",
"new",
"popularity",
"model",
"matching",
"the",
"data",
"set",
"this",
"model",
"was",
"trained",
"with",
".",
"Can",
"be",
"used",
"for",
"comparison",
"purposes",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1763-L1772 | train | Returns a new PopularityRecommender object that is trained with the data set this model was
trained with. Can be used for comparison purposes. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender._get_item_intersection_info | def _get_item_intersection_info(self, item_pairs):
"""
For a collection of item -> item pairs, returns information about the
users in that intersection.
Parameters
----------
item_pairs : 2-column SFrame of two item columns, or a list of
(item_1, item_2) tupl... | python | def _get_item_intersection_info(self, item_pairs):
"""
For a collection of item -> item pairs, returns information about the
users in that intersection.
Parameters
----------
item_pairs : 2-column SFrame of two item columns, or a list of
(item_1, item_2) tupl... | [
"def",
"_get_item_intersection_info",
"(",
"self",
",",
"item_pairs",
")",
":",
"if",
"type",
"(",
"item_pairs",
")",
"is",
"list",
":",
"if",
"not",
"all",
"(",
"type",
"(",
"t",
")",
"in",
"[",
"list",
",",
"tuple",
"]",
"and",
"len",
"(",
"t",
"... | For a collection of item -> item pairs, returns information about the
users in that intersection.
Parameters
----------
item_pairs : 2-column SFrame of two item columns, or a list of
(item_1, item_2) tuples.
Returns
-------
out : SFrame
A ... | [
"For",
"a",
"collection",
"of",
"item",
"-",
">",
"item",
"pairs",
"returns",
"information",
"about",
"the",
"users",
"in",
"that",
"intersection",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1774-L1809 | train | Returns information about the items in that intersection. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/recommender/util.py | _Recommender.export_coreml | def export_coreml(self, filename):
"""
Export the model in Core ML format.
Parameters
----------
filename: str
A valid filename where the model can be saved.
Examples
--------
>>> model.export_coreml('myModel.mlmodel')
"""
print... | python | def export_coreml(self, filename):
"""
Export the model in Core ML format.
Parameters
----------
filename: str
A valid filename where the model can be saved.
Examples
--------
>>> model.export_coreml('myModel.mlmodel')
"""
print... | [
"def",
"export_coreml",
"(",
"self",
",",
"filename",
")",
":",
"print",
"(",
"'This model is exported as a custom Core ML model. In order to use it in your\\n'",
"'application, you must also include \"libRecommender.dylib\". For additional\\n'",
"'details see:\\n'",
"'https://apple.github... | Export the model in Core ML format.
Parameters
----------
filename: str
A valid filename where the model can be saved.
Examples
--------
>>> model.export_coreml('myModel.mlmodel') | [
"Export",
"the",
"model",
"in",
"Core",
"ML",
"format",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L1811-L1830 | train | Export the model in Core ML format. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/regression/random_forest_regression.py | RandomForestRegression.evaluate | def evaluate(self, dataset, metric='auto', missing_value_action='auto'):
"""
Evaluate the model on the given dataset.
Parameters
----------
dataset : SFrame
Dataset in the same format used for training. The columns names and
types of the dataset must be ... | python | def evaluate(self, dataset, metric='auto', missing_value_action='auto'):
"""
Evaluate the model on the given dataset.
Parameters
----------
dataset : SFrame
Dataset in the same format used for training. The columns names and
types of the dataset must be ... | [
"def",
"evaluate",
"(",
"self",
",",
"dataset",
",",
"metric",
"=",
"'auto'",
",",
"missing_value_action",
"=",
"'auto'",
")",
":",
"_raise_error_evaluation_metric_is_valid",
"(",
"metric",
",",
"[",
"'auto'",
",",
"'rmse'",
",",
"'max_error'",
"]",
")",
"retu... | Evaluate the model on the given dataset.
Parameters
----------
dataset : SFrame
Dataset in the same format used for training. The columns names and
types of the dataset must be the same as that used in training.
metric : str, optional
Name of the ev... | [
"Evaluate",
"the",
"model",
"on",
"the",
"given",
"dataset",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/regression/random_forest_regression.py#L179-L228 | train | Evaluate the model on the given dataset. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/unity/python/turicreate/toolkits/regression/random_forest_regression.py | RandomForestRegression.predict | def predict(self, dataset, missing_value_action='auto'):
"""
Predict the target column of the given dataset.
The target column is provided during
:func:`~turicreate.random_forest_regression.create`. If the target column is in the
`dataset` it will be ignored.
Parameters... | python | def predict(self, dataset, missing_value_action='auto'):
"""
Predict the target column of the given dataset.
The target column is provided during
:func:`~turicreate.random_forest_regression.create`. If the target column is in the
`dataset` it will be ignored.
Parameters... | [
"def",
"predict",
"(",
"self",
",",
"dataset",
",",
"missing_value_action",
"=",
"'auto'",
")",
":",
"return",
"super",
"(",
"RandomForestRegression",
",",
"self",
")",
".",
"predict",
"(",
"dataset",
",",
"output_type",
"=",
"'margin'",
",",
"missing_value_ac... | Predict the target column of the given dataset.
The target column is provided during
:func:`~turicreate.random_forest_regression.create`. If the target column is in the
`dataset` it will be ignored.
Parameters
----------
dataset : SFrame
A dataset that has the... | [
"Predict",
"the",
"target",
"column",
"of",
"the",
"given",
"dataset",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/regression/random_forest_regression.py#L230-L272 | train | Predict the target column of the given dataset. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/feature_vectorizer.py | create_feature_vectorizer | def create_feature_vectorizer(input_features, output_feature_name,
known_size_map = {}):
"""
Creates a feature vectorizer from input features, return the spec for
a feature vectorizer that puts everything into a single array of length
equal to the total size of all the inpu... | python | def create_feature_vectorizer(input_features, output_feature_name,
known_size_map = {}):
"""
Creates a feature vectorizer from input features, return the spec for
a feature vectorizer that puts everything into a single array of length
equal to the total size of all the inpu... | [
"def",
"create_feature_vectorizer",
"(",
"input_features",
",",
"output_feature_name",
",",
"known_size_map",
"=",
"{",
"}",
")",
":",
"spec",
"=",
"_Model_pb2",
".",
"Model",
"(",
")",
"spec",
".",
"specificationVersion",
"=",
"SPECIFICATION_VERSION",
"input_featur... | Creates a feature vectorizer from input features, return the spec for
a feature vectorizer that puts everything into a single array of length
equal to the total size of all the input features. Returns a 2-tuple
`(spec, num_dimension)`
Parameters
----------
input_features: [list of 2-tuples]
... | [
"Creates",
"a",
"feature",
"vectorizer",
"from",
"input",
"features",
"return",
"the",
"spec",
"for",
"a",
"feature",
"vectorizer",
"that",
"puts",
"everything",
"into",
"a",
"single",
"array",
"of",
"length",
"equal",
"to",
"the",
"total",
"size",
"of",
"al... | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/feature_vectorizer.py#L15-L94 | train | Creates a feature vectorizer from input features and outputs the output feature name. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
apple/turicreate | deps/src/boost_1_68_0/libs/predef/tools/ci/common.py | utils.query_boost_version | def query_boost_version(boost_root):
'''
Read in the Boost version from a given boost_root.
'''
boost_version = None
if os.path.exists(os.path.join(boost_root,'Jamroot')):
with codecs.open(os.path.join(boost_root,'Jamroot'), 'r', 'utf-8') as f:
for lin... | python | def query_boost_version(boost_root):
'''
Read in the Boost version from a given boost_root.
'''
boost_version = None
if os.path.exists(os.path.join(boost_root,'Jamroot')):
with codecs.open(os.path.join(boost_root,'Jamroot'), 'r', 'utf-8') as f:
for lin... | [
"def",
"query_boost_version",
"(",
"boost_root",
")",
":",
"boost_version",
"=",
"None",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"boost_root",
",",
"'Jamroot'",
")",
")",
":",
"with",
"codecs",
".",
"open",
"("... | Read in the Boost version from a given boost_root. | [
"Read",
"in",
"the",
"Boost",
"version",
"from",
"a",
"given",
"boost_root",
"."
] | 74514c3f99e25b46f22c6e02977fe3da69221c2e | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/boost_1_68_0/libs/predef/tools/ci/common.py#L421-L435 | train | Read in the Boost version from a given boost_root. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.