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- from libc.stdint cimport int16_t, int32_t, uint64_t
- from preshed.maps cimport MapStruct
- from libcpp.vector cimport vector
- from libc.stdlib cimport malloc, calloc, free, realloc
- from libc.string cimport memcpy, memset
- from murmurhash.mrmr cimport real_hash64 as hash64
-
- from .typedefs cimport len_t, idx_t, atom_t, weight_t
- from .linalg cimport VecVec
-
-
- include "compile_time_constants.pxi"
-
- ctypedef vector[weight_t] vector_weight_t
-
-
- ctypedef void (*do_update_t)(
- weight_t* weights,
- weight_t* gradient,
- len_t nr,
- const ConstantsC* hp,
- ) nogil
-
-
- ctypedef void (*do_feed_fwd_t)(
- weight_t** fwd,
- const weight_t* W,
- const len_t* shape,
- int nr_layer,
- int nr_batch,
- const ConstantsC* hp
- ) nogil
-
-
- ctypedef void (*do_feed_bwd_t)(
- weight_t* G,
- weight_t** bwd,
- const weight_t* W,
- const weight_t* const* fwd,
- const len_t* shape,
- int nr_layer,
- int nr_batch,
- const ConstantsC* hp
- ) nogil
-
-
- # Alias this, so that it matches our naming scheme
- ctypedef MapStruct MapC
-
-
- cdef struct ConstantsC:
- weight_t a
- weight_t b
- weight_t c
- weight_t d
- weight_t e
- weight_t g
- weight_t h
- weight_t i
- weight_t j
- weight_t k
- weight_t l
- weight_t m
- weight_t n
- weight_t o
- weight_t p
- weight_t q
- weight_t r
- weight_t s
- weight_t t
- weight_t u
- weight_t w
- weight_t x
- weight_t y
- weight_t z
-
-
- cdef struct EmbedC:
- MapC** weights
- MapC** gradients
- weight_t** defaults
- weight_t** d_defaults
- idx_t* offsets
- len_t* lengths
- len_t nr
- int nr_support
-
-
- cdef struct NeuralNetC:
- do_feed_fwd_t feed_fwd
- do_feed_bwd_t feed_bwd
- do_update_t update
-
- len_t* widths
- weight_t* weights
- weight_t* gradient
-
- EmbedC* embed
-
- len_t nr_layer
- len_t nr_weight
- len_t nr_node
-
- ConstantsC hp
-
-
- cdef extern from "stdlib.h":
- int posix_memalign(void **memptr, size_t alignment, size_t size) nogil
- void* valloc (size_t size) nogil
-
-
- cdef struct ExampleC:
- int* is_valid
- weight_t* costs
- uint64_t* atoms
- FeatureC* features
- weight_t* scores
-
- int nr_class
- int nr_atom
- int nr_feat
-
-
- cdef cppclass MinibatchC:
- weight_t** _fwd
- weight_t** _bwd
-
- FeatureC** _feats
- len_t* _nr_feat
-
- weight_t* _costs
- int* _is_valid
- uint64_t* signatures
-
- len_t* widths
- int i
- int nr_layer
- int batch_size
-
- __init__(len_t* widths, int nr_layer, int batch_size) nogil:
- this.i = 0
- this.nr_layer = nr_layer
- this.batch_size = batch_size
- this.widths = <len_t*>calloc(nr_layer, sizeof(len_t))
- this._fwd = <weight_t**>calloc(nr_layer, sizeof(weight_t*))
- this._bwd = <weight_t**>calloc(nr_layer, sizeof(weight_t*))
- for i in range(nr_layer):
- this.widths[i] = widths[i]
- this._fwd[i] = <weight_t*>calloc(this.widths[i] * batch_size, sizeof(weight_t))
- this._bwd[i] = <weight_t*>calloc(this.widths[i] * batch_size, sizeof(weight_t))
- this._feats = <FeatureC**>calloc(batch_size, sizeof(void*))
- this._nr_feat = <len_t*>calloc(batch_size, sizeof(len_t))
- this._is_valid = <int*>calloc(batch_size * widths[nr_layer-1], sizeof(int))
- this._costs = <weight_t*>calloc(batch_size * widths[nr_layer-1], sizeof(weight_t))
- this.signatures = <uint64_t*>calloc(batch_size, sizeof(uint64_t))
-
- __dealloc__() nogil:
- free(this.widths)
- for i in range(this.nr_layer):
- free(this._fwd[i])
- free(this._bwd[i])
- for i in range(this.i):
- free(this._feats[i])
- free(this._fwd)
- free(this._bwd)
- free(this._feats)
- free(this._nr_feat)
- free(this._is_valid)
- free(this._costs)
- free(this.signatures)
-
- void reset() nogil:
- for i in range(this.nr_layer):
- memset(this._fwd[i],
- 0, sizeof(this._fwd[i][0]) * this.batch_size * this.widths[i])
- memset(this._bwd[i],
- 0, sizeof(this._bwd[i][0]) * this.batch_size * this.widths[i])
- memset(this._nr_feat, 0, sizeof(this._nr_feat[0]) * this.batch_size)
- memset(this.signatures, 0, sizeof(this.signatures[0]) * this.batch_size)
- memset(this._costs,
- 0, sizeof(this._costs[0]) * this.nr_out() * this.batch_size)
- memset(this._is_valid,
- 0, sizeof(this._is_valid[0]) * this.nr_out() * this.batch_size)
- for i in range(this.i):
- free(this._feats[i])
- this._feats[i] = NULL
- this.i = 0
-
- int nr_in() nogil:
- return this.widths[0]
-
- int nr_out() nogil:
- return this.widths[this.nr_layer - 1]
-
- int push_back(const FeatureC* feats, int nr_feat,
- const weight_t* costs, const int* is_valid, uint64_t key) nogil:
- # Hash the features, to see if the batch has a matching input.
- # If it does, just update the gradient for it.
- if key != 0:
- for i in range(this.i):
- if this.signatures[i] == key:
- VecVec.add_i(this.costs(i),
- costs, 1.0, this.nr_out())
- return 0
- if this.i >= this.batch_size:
- this.reset()
- this.i = 0 # This is done in reset() --- but make it obvious
-
- this.signatures[this.i] = key
- this._nr_feat[this.i] = nr_feat
- this._feats[this.i] = <FeatureC*>calloc(nr_feat, sizeof(FeatureC))
- memcpy(this._feats[this.i],
- feats, nr_feat * sizeof(this._feats[this.i][0]))
-
- memcpy(this.costs(this.i),
- costs, this.nr_out() * sizeof(costs[0]))
- if is_valid is not NULL:
- memcpy(this.is_valid(this.i),
- is_valid, this.nr_out() * sizeof(is_valid[0]))
- else:
- for i in range(this.nr_out()):
- this.is_valid(this.i)[i] = 1
- this.i += 1
- return this.i >= this.batch_size
-
- FeatureC* features(int i) nogil:
- return this._feats[i]
-
- int nr_feat(int i) nogil:
- return this._nr_feat[i]
-
- weight_t* fwd(int i, int j) nogil:
- return this._fwd[i] + (j * this.widths[i])
-
- weight_t* bwd(int i, int j) nogil:
- return this._bwd[i] + (j * this.widths[i])
-
- weight_t* scores(int i) nogil:
- return this.fwd(this.nr_layer-1, i)
-
- weight_t* losses(int i) nogil:
- return this.bwd(this.nr_layer-1, i)
-
- weight_t* costs(int i) nogil:
- return this._costs + (i * this.nr_out())
-
- int* is_valid(int i) nogil:
- return this._is_valid + (i * this.nr_out())
-
- int guess(int i) nogil:
- return VecVec.arg_max_if_true(this.scores(i), this.is_valid(i), this.nr_out())
-
- int best(int i) nogil:
- return VecVec.arg_max_if_zero(this.scores(i), this.costs(i), this.nr_out())
-
-
-
- cdef packed struct SparseArrayC:
- int32_t key
- weight_t val
-
-
- cdef struct FeatureC:
- int i
- uint64_t key
- weight_t value
-
-
- cdef struct SparseAverageC:
- SparseArrayC* curr
- SparseArrayC* mom1
- SparseArrayC* mom2
- SparseArrayC* avgs
- SparseArrayC* times
- SparseArrayC* penalties
- weight_t penalty
-
-
- cdef struct TemplateC:
- int[MAX_TEMPLATE_LEN] indices
- int length
- atom_t[MAX_TEMPLATE_LEN] atoms
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